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What is elevation mapping cupy +| :doc:`getting_started/installation` - How to install the elevation map +| :doc:`getting_started/tutorial` - How to launch the first elevation map + + +This is a ROS package for elevation mapping on GPU. The elevation mapping code is written in python and uses cupy for GPU computation. The +plane segmentation is done independently and runs on CPU. When the plane segmentation is generated, local convex approximations of the +terrain can be efficiently generated. + +.. image:: ../media/main_repo.png + :alt: Elevation map examples +.. image:: ../media/main_mem.png + :alt: Overview of the project + + +Citing +--------------- +If you use the elevation mapping cupy, please cite the following paper: +Elevation Mapping for Locomotion and Navigation using GPU + +.. hint:: + + Elevation Mapping for Locomotion and Navigation using GPU `Link `_ + + Takahiro Miki, Lorenz Wellhausen, Ruben Grandia, Fabian Jenelten, Timon Homberger, Marco Hutter + +.. code-block:: + + @misc{mikielevation2022, + doi = {10.48550/ARXIV.2204.12876}, + author = {Miki, Takahiro and Wellhausen, Lorenz and Grandia, Ruben and Jenelten, Fabian and Homberger, Timon and Hutter, Marco}, + keywords = {Robotics (cs.RO), FOS: Computer and information sciences, FOS: Computer and information sciences}, + title = {Elevation Mapping for Locomotion and Navigation using GPU}, + publisher = {International Conference on Intelligent Robots and Systems (IROS)}, + year = {2022}, + } + +Multi-modal elevation mapping if you use color or semantic layers + +.. hint:: + + MEM: Multi-Modal Elevation Mapping for Robotics and Learning `Link `_ + + Gian Erni, Jonas Frey, Takahiro Miki, Matias Mattamala, Marco Hutter + +.. code-block:: + + @misc{Erni2023-bs, + title = "{MEM}: {Multi-Modal} Elevation Mapping for Robotics and Learning", + author = "Erni, Gian and Frey, Jonas and Miki, Takahiro and Mattamala, Matias and Hutter, Marco", + publisher = {International Conference on Intelligent Robots and Systems (IROS)}, + year = {2023}, + } diff --git a/_sources/getting_started/cuda_installation.rst.txt b/_sources/getting_started/cuda_installation.rst.txt new file mode 100644 index 00000000..0c4ede99 --- /dev/null +++ b/_sources/getting_started/cuda_installation.rst.txt @@ -0,0 +1,40 @@ +Cuda installation +================================================================== +.. _cuda_installation: + + +CUDA +------------------------------------------------------------------- + +You can download CUDA10.2 from `here `_. +You can follow the instruction. + +.. code-block:: bash + + wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin + + sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600 + + sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub + + sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ /" + + sudo apt-get update + + sudo apt-get -y install cuda + + +cuDNN +------------------------------------------------------------------- + +You can download specific version from `here `_. +For example, the tested version is with `libcudnn8_8.0.0.180-1+cuda10.2_amd64.deb`. + +Then install them using the command below. + +.. code-block:: bash + + sudo dpkg -i libcudnn8_8.0.0.180-1+cuda10.2_amd64.deb + + sudo dpkg -i libcudnn8-dev_8.0.0.180-1+cuda10.2_amd64.deb + diff --git a/_sources/getting_started/installation.rst.txt b/_sources/getting_started/installation.rst.txt new file mode 100644 index 00000000..95a99a2d --- /dev/null +++ b/_sources/getting_started/installation.rst.txt @@ -0,0 +1,275 @@ +.. _installation: + + +Installation +****************************************************************** + +This section provides instructions for installing the necessary dependencies for the project. The installation process includes setting up CUDA & cuDNN, installing Python dependencies, and configuring Cupy. +Follow the instructions carefully to avoid any installation issues. + + +Dockers +================================================================== +We provide a docker setup for the project. +To build the docker image, run the following command: + + +.. code-block:: bash + + cd /docker + ./build.sh + + +To run the docker image, run the following command: + + +.. code-block:: bash + + cd /docker + ./run.sh + +This will start the docker container and mount the home directory of the host machine to the docker container. +After you clone the project repository into your catkin_ws, you can build the packages inside the docker container. +To build the packages inside the docker container, follow the instructions in the `Build section <#build>`_ of this document. + + +On Desktop or Laptop with NVIDIA GPU +================================================================== + +CUDA & cuDNN +------------------------------------------------------------------ + +If you do not have CUDA and cuDNN installed, please install them first. +The tested versions are CUDA10.2, 11.6 + +`CUDA `_ +`cuDNN `_ + + +You can check how to install :ref:`here`. + +Python dependencies +------------------------------------------------------------------ + +You will need + +* `cupy `_ +* `numpy `_ +* `scipy `_ +* `shapely==1.7.1 `_ + +For traversability filter, either of + +* `torch `_ +* `chainer `_ + +Optionally, OpenCV for inpainting filter. + +* `opencv-python `_ + +Install `numpy`, `scipy`, `shapely`, `opencv-python` with the following command. + +.. code-block:: bash + + pip3 install -r requirements.txt + + +Cupy +------------------------------------------------------------------- + + +cupy can be installed with specific CUDA versions. (On jetson, only "from source" i.e. `pip install cupy` could work) +For CUDA 10.2 + +.. code-block:: bash + + pip install cupy-cuda102 + +For CUDA 11.0 + +.. code-block:: bash + + pip install cupy-cuda110 + +For CUDA 11.1 + +.. code-block:: bash + + pip install cupy-cuda111 + +For CUDA 11.2 + +.. code-block:: bash + + pip install cupy-cuda112 + +For CUDA 11.3 + +.. code-block:: bash + + pip install cupy-cuda113 + +For CUDA 11.4 + +.. code-block:: bash + + pip install cupy-cuda114 + +For CUDA 11.5 + +.. code-block:: bash + + pip install cupy-cuda115 + +For CUDA 11.6 + +.. code-block:: bash + + pip install cupy-cuda116 + +(Install CuPy from source) + +.. code-block:: bash + + pip install cupy + +Traversability filter +------------------------------------------------------------------- + +You can choose either pytorch, or chainer to run the CNN based traversability filter. +Install by following the official documents. + +* `torch `_ +* `chainer `_ + +Pytorch uses ~2GB more GPU memory than Chainer, but runs a bit faster. +Use parameter `use_chainer` to select which backend to use. + +ROS package dependencies +------------------------------------------------------------------- + +* `pybind11_catkin `_ +* `grid_map `_ + +.. code-block:: bash + + sudo apt install ros-noetic-pybind11-catkin + sudo apt install ros-noetic-grid-map-core ros-noetic-grid-map-msgs + + +On Jetson +================================================================== + +CUDA CuDNN +------------------------------------------------------------------- + +`CUDA` and `cuDNN` can be installed via apt. It comes with nvidia-jetpack. The tested version is jetpack 4.5 with L4T 32.5.0. + +Python dependencies +------------------------------------------------------------------- + +On jetson, you need the version for its CPU arch: + +.. code-block:: bash + + wget https://nvidia.box.com/shared/static/p57jwntv436lfrd78inwl7iml6p13fzh.whl -O torch-1.8.0-cp36-cp36m-linux_aarch64.whl + pip3 install Cython + pip3 install numpy==1.19.5 torch-1.8.0-cp36-cp36m-linux_aarch64.whl + + +Also, you need to install cupy with + +.. code-block:: bash + + pip3 install cupy + + +This builds the packages from source so it would take time. + +ROS dependencies +----------------------- + +* `pybind11_catkin `_ +* `grid_map `_ + +.. code-block:: bash + + sudo apt install ros-melodic-pybind11-catkin + sudo apt install ros-melodic-grid-map-core ros-melodic-grid-map-msgs + + +Also, on jetson you need fortran (should already be installed). + +.. code-block:: bash + + sudo apt install gfortran + + +If the Jetson is set up with Jetpack 4.5 with ROS Melodic the following package is additionally required: + +.. code-block:: bash + + git clone git@github.com:ros/filters.git -b noetic-devel + + +Plane segmentation dependencies +================================================================== + +OpenCV +------------------------------------------------------------------- + +.. code-block:: bash + + sudo apt install libopencv-dev + +Eigen +------------------------------------------------------------------- + +.. code-block:: bash + + sudo apt install libeigen3-dev + +CGAL +------------------------------------------------------------------- + +CGAL5 is required. It will be automatically downloaded and installed into the catkin workspace by the cgal5_catkin package. Make sure you +have the third-party libaries installed on you machine: + +.. code-block:: bash + + sudo apt install libgmp-dev + sudo apt install libmpfr-dev + sudo apt install libboost-all-dev + + +Semantic Sensors +================================================================== +Elevation mapping node can receive multi-modal point cloud and image topics. +In this example, we use semantic segmentation models to process color images and publish those topics. + +Python dependencies +------------------------------------------------------------------- + +.. code-block:: bash + + pip3 install torchvision scikit-learn + +Detectron + +.. code-block:: bash + + python3 -m pip install 'git+https://github.com/facebookresearch/detectron2.git' + + +Build +================================================================== +After installing all the dependencies, you can build the packages. +Clone the project repository into your catkin_ws/src directory. +Then, build the packages with catkin. + +.. code-block:: bash + + cd + catkin build elevation_mapping_cupy # The core package + catkin build convex_plane_decomposition_ros # If you want to use plane segmentation + catkin build semantic_sensor # If you want to use semantic sensors \ No newline at end of file diff --git a/_sources/getting_started/introduction.rst.txt b/_sources/getting_started/introduction.rst.txt new file mode 100644 index 00000000..90689dfe --- /dev/null +++ b/_sources/getting_started/introduction.rst.txt @@ -0,0 +1,132 @@ +.. _introduction: + + + +Introduction +****************************************************************** +The Elevaton Mapping CuPy software package represents an advancement in robotic navigation and locomotion. +Integrating with the Robot Operating System (ROS) and utilizing GPU acceleration, this framework enhances point cloud registration and ray casting, +crucial for efficient and accurate robotic movement, particularly in legged robots. + +Used for Various Real-World Applications +------------------------------------------------------------------- +This software package has been rigorously tested in challenging environments, including the DARPA Subterranean Challenge, +demonstrating its effectiveness in complex, real-world scenarios. +It supports a wide range of applications, from underground exploration to advanced research in legged locomotion and autonomous navigation. + +* **DARPA Subterranean Challenge**: This package was used by Team CERBERUS in the DARPA Subterranean Challenge. + + `Team Cerberus `_ + + `CERBERUS in the DARPA Subterranean Challenge (Science Robotics) `_ + +* **ESA / ESRIC Space Resources Challenge**: This package was used for the Space Resources Challenge. + + `Scientific exploration of challenging planetary analog environments with a team of legged robots (Science Robotics) `_ + + + + +Key Features +------------------------------------------------------------------- +* **Height Drift Compensation**: Tackles state estimation drifts that can create mapping artifacts, ensuring more accurate terrain representation. + +* **Visibility Cleanup and Artifact Removal**: Raycasting methods and an exclusion zone feature are designed to remove virtual artifacts and correctly interpret overhanging obstacles, preventing misidentification as walls. + +* **Learning-based Traversability Filter**: Assesses terrain traversability using local geometry, improving path planning and navigation. + +* **Versatile Locomotion Tools**: Incorporates smoothing filters and plane segmentation, optimizing movement across various terrains. + +* **Multi-Modal Elevation Map (MEM) Framework**: Allows seamless integration of diverse data like geometry, semantics, and RGB information, enhancing multi-modal robotic perception. + +* **GPU-Enhanced Efficiency**: Facilitates rapid processing of large data structures, crucial for real-time applications. + +Overview +------------------------------------------------------------------- + +.. image:: ../../media/overview.png + :alt: Overview of multi-modal elevation map structure + +Overview of our multi-modal elevation map structure. The framework takes multi-modal images (purple) and multi-modal (blue) point clouds as +input. This data is input into the elevation map by first associating the data to the cells and then fused with different fusion algorithms into the various +layers of the map. Finally the map can be post-processed with various custom plugins to generate new layers (e.g. traversability) or process layer for +external components (e.g. line detection). + +Subscribed Topics +------------------------------------------------------------------- +The subscribed topics are specified under **subscribers** parameter. + +Example setup is in **elevation_mapping_cupy/config/core/example_setup.yaml**. + +* **/** ([sensor_msgs/PointCloud2]) + + The point cloud topic. It can have additional channels for RGB, intensity, etc. + +* **/** ([sensor_msgs/Image]) + + The image topic. It can have additional channels for RGB, semantic probabilities, image features etc. + +* **/** ([sensor_msgs/CameraInfo]) + + The camera info topic. It is used to project the point cloud into the image plane. + +* **/** ([elevation_map_msgs/ChannelInfo]) + + If this topic is configured, the node will subscribe to it and use the information to associate the image channels to the elevation map layers. + +* **/tf** ([tf/tfMessage]) + + The transformation tree. + +* The plane segmentation node subscribes to an elevation map topic ([grid_map_msg/GridMap]). This can be configured in + **convex_plane_decomposition_ros/config/core/parameters.yaml** + +Published Topics +------------------------------------------------------------------- +For elevation_mapping_cupy, topics are published as set in the rosparam. +You can specify which layers to publish in which fps. + +Under publishers, you can specify the topic_name, layers basic_layers and fps. + +.. code-block:: yaml + + publishers: + your_topic_name: + layers: [ 'list_of_layer_names', 'layer1', 'layer2' ] # Choose from 'elevation', 'variance', 'traversability', 'time' + plugin layers + basic_layers: [ 'list of basic layers', 'layer1' ] # basic_layers for valid cell computation (e.g. Rviz): Choose a subset of `layers`. + fps: 5.0 # Publish rate. Use smaller value than `map_acquire_fps`. + + +Example setting in `config/parameters.yaml`. + +* **elevation_map_raw** ([grid_map_msg/GridMap]) + + The entire elevation map. + +* **elevation_map_recordable** ([grid_map_msg/GridMap]) + + The entire elevation map with slower update rate for visualization and logging. + +* **elevation_map_filter** ([grid_map_msg/GridMap]) + + The filtered maps using plugins. + +The plane segmentation node publishes the following: + +* **planar_terrain** ([convex_plane_decomposition_msgs/PlanarTerrain]) + + A custom message that contains the full segmentation as a map together with the boundary information. + +* **filtered_map** ([grid_map_msg/GridMap]) + + A grid map message to visualize the segmentation and some intermediate results. This information is also part of **planar_terrain**. + +* **boundaries** ([visualization_msgs/MarkerArray]) + + A set of polygons that trace the boundaries of the segmented region. Holes and boundaries of a single region are published as separate + markers with the same color. + +* **insets** ([visualization_msgs/PolygonArray]) + + A set of polygons that are at a slight inward offset from **boundaries**. There might be more insets than boundaries since the inward + shift can cause a single region to break down into multiple when narrow passages exist. diff --git a/_sources/getting_started/tutorial.rst.txt b/_sources/getting_started/tutorial.rst.txt new file mode 100644 index 00000000..12f9eda3 --- /dev/null +++ b/_sources/getting_started/tutorial.rst.txt @@ -0,0 +1,127 @@ +.. _tutorial: + +Tutorial +****************************************************************** +This tutorial will guide you through the basic usage of the elevation mapping cupy. +You will learn how to run the plane segmentation node, the sensor node, and the TurtleBot example. + +If you want to use your own custom plugins, please refer to the :ref:`plugins`. + + +Run +================================================================== + +Basic usage. + +.. code-block:: bash + + roslaunch elevation_mapping_cupy elevation_mapping_cupy.launch + + +For the plane segmentation node + +.. code-block:: bash + + roslaunch convex_plane_decomposition_ros convex_plane_decomposition.launch + +For the sensor node + +.. code-block:: bash + + roslaunch semantic_sensor semantic_pointcloud.launch + roslaunch semantic_sensor semantic_image.launch + + +Run TurtleBot example +================================================================== + +First, install turtlebot simulation. + +.. code-block:: bash + + sudo apt install ros-noetic-turtlebot3-gazebo ros-noetic-turtlebot3-teleop + + +Then, you can run the examples. For the basic version: + +.. code-block:: bash + + export TURTLEBOT3_MODEL=waffle + roslaunch elevation_mapping_cupy turtlesim_simple_example.launch + + +For fusing semantics into the map such as rgb from a multi modal pointcloud: + +.. image:: ../../media/turtlebot.png + :alt: Elevation map examples + +.. code-block:: bash + + export TURTLEBOT3_MODEL=waffle + roslaunch elevation_mapping_cupy turtlesim_semantic_pointcloud_example.launch + +For fusing semantics into the map such as rgb semantics or features from an image: + +.. code-block:: bash + + export TURTLEBOT3_MODEL=waffle + roslaunch elevation_mapping_cupy turtlesim_semantic_image_example.launch + +Or, for the version including plane segmentation: + +.. code-block:: bash + + catkin build convex_plane_decomposition_ros + export TURTLEBOT3_MODEL=waffle + roslaunch elevation_mapping_cupy turtlesim_plane_decomposition_example.launch + + +To control the robot with a keyboard, a new terminal window needs to be opened. +Then run + +.. code-block:: bash + + export TURTLEBOT3_MODEL=waffle + roslaunch turtlebot3_teleop turtlebot3_teleop_key.launch + + +Velocity inputs can be sent to the robot by pressing the keys `a`, `w`, `d`, `x`. To stop the robot completely, press `s`. + + + + +Errors +================================================================== + +If you build with the install flag under ros melodic, you might get issues with the modules not found: + +.. code-block:: bash + + terminate called after throwing an instance of 'pybind11::error_already_set' + what(): ModuleNotFoundError: No module named 'elevation_mapping_cupy' + +This is because python3 modules are installed into a different location. + +This can be fixed by including also the python3 modules location in the `PYTHONPATH` by adding following line into the launch file: + +.. code-block:: xml + + + +If you get error such as + +.. code-block:: none + + Make Error at /usr/share/cmake-3.16/Modules/FindPackageHandleStandardArgs.cmake:146 (message): + Could NOT find PythonInterp: Found unsuitable version "2.7.18", but + required is at least "3" (found /usr/bin/python) + + +Build with option. + +.. code-block:: bash + + catkin build elevation_mapping_cupy -DPYTHON_EXECUTABLE=$(which python3) + + + diff --git a/_sources/index.rst.txt b/_sources/index.rst.txt new file mode 100644 index 00000000..d6566c77 --- /dev/null +++ b/_sources/index.rst.txt @@ -0,0 +1,39 @@ +.. include:: documentation.rst + +.. toctree:: + :maxdepth: 1 + :caption: Overview + + +.. toctree:: + :hidden: + :maxdepth: 3 + :caption: Getting Started + + Introduction + Installation + Tutorial + +.. toctree:: + :hidden: + :maxdepth: 2 + :caption: Usage + + Plugins + Parameters + Plane Segmentation + Semantics + + +.. toctree:: + :hidden: + :maxdepth: 3 + :caption: Library + + Python + + + + + + diff --git a/_sources/python/elevation_mapping.rst.txt b/_sources/python/elevation_mapping.rst.txt new file mode 100644 index 00000000..03bb1e28 --- /dev/null +++ b/_sources/python/elevation_mapping.rst.txt @@ -0,0 +1,29 @@ +.. _elevation_mapping: + +Elevation mapping cupy +****************************************************************** + +.. automodule:: elevation_mapping_cupy.elevation_mapping + :members: + :undoc-members: + :show-inheritance: + +.. automodule:: elevation_mapping_cupy.semantic_map + :members: + :undoc-members: + :show-inheritance: + +.. automodule:: elevation_mapping_cupy.parameter + :members: + :undoc-members: + :show-inheritance: + +.. automodule:: elevation_mapping_cupy.plugins.plugin_manager + :members: + :undoc-members: + :show-inheritance: + +.. automodule:: elevation_mapping_cupy.fusion + :members: + :undoc-members: + :show-inheritance: diff --git a/_sources/python/index.rst.txt b/_sources/python/index.rst.txt new file mode 100644 index 00000000..d2eb5593 --- /dev/null +++ b/_sources/python/index.rst.txt @@ -0,0 +1,8 @@ +Python software +****************************************************************** + +.. toctree:: + elevation_mapping + semantic_sensor + + diff --git a/_sources/python/semantic_sensor.rst.txt b/_sources/python/semantic_sensor.rst.txt new file mode 100644 index 00000000..37904e19 --- /dev/null +++ b/_sources/python/semantic_sensor.rst.txt @@ -0,0 +1,47 @@ +.. _semantic_sensor: + +Semantic Pointcloud +****************************************************************** + + +.. automodule:: semantic_sensor.pointcloud_node + :members: + :undoc-members: + :show-inheritance: + + +.. automodule:: semantic_sensor.pointcloud_parameters + :members: + :undoc-members: + :show-inheritance: + +.. automodule:: semantic_sensor.image_node + :members: + :undoc-members: + :show-inheritance: + + +.. automodule:: semantic_sensor.image_parameters + :members: + :undoc-members: + :show-inheritance: + +.. automodule:: semantic_sensor.networks + :members: + :undoc-members: + :show-inheritance: + + +.. automodule:: semantic_sensor.utils + :members: + :undoc-members: + :show-inheritance: + + + + + + + + + diff --git a/_sources/usage/parameters.rst.txt b/_sources/usage/parameters.rst.txt new file mode 100644 index 00000000..0594a0f4 --- /dev/null +++ b/_sources/usage/parameters.rst.txt @@ -0,0 +1,46 @@ +.. _parameters: + +Parameters +****************************************************************** + +There are three parameter files: + +#. `Robot Setup Configurations`_ + +#. `Plugin configurations`_ + +#. `Core Parameters`_ + +#. `Sensor parameter`_ + + +Robot Setup Configurations +================================================ +Such as Publishers and subscribers + +.. include:: ../../../elevation_mapping_cupy/config/core/example_setup.yaml + :code: yaml + +Plugin configurations +================================================ + +More informations on the plugins can be found in :ref:`plugins`. + +.. include:: ../../../elevation_mapping_cupy/config/core/plugin_config.yaml + :code: yaml + +Core Parameters +============================================================== + +.. include:: ../../../elevation_mapping_cupy/config/core/core_param.yaml + :code: yaml + +Sensor parameter +================================================ + +More informations on the sensor configurations can be found in :ref:`semantics`. + +.. include:: ../../../sensor_processing/semantic_sensor/config/sensor_parameter.yaml + :code: yaml + + diff --git a/_sources/usage/plane_segmentation.rst.txt b/_sources/usage/plane_segmentation.rst.txt new file mode 100644 index 00000000..35c2efd7 --- /dev/null +++ b/_sources/usage/plane_segmentation.rst.txt @@ -0,0 +1,7 @@ +.. _plane_segmentation: + +Plane Segmentation +****************************************************************** + +.. image:: ../media/convex_approximation.gif + :alt: Convex approximation diff --git a/_sources/usage/plugins.rst.txt b/_sources/usage/plugins.rst.txt new file mode 100644 index 00000000..4a3f6d9b --- /dev/null +++ b/_sources/usage/plugins.rst.txt @@ -0,0 +1,127 @@ +.. _plugins: + +Plugins +****************************************************************** + +You can add your own plugin to process the elevation map and publish as a layer in GridMap message. + +This page is structured in two parts: + +* `Create a plugin`_ + +* `Existing plugins`_ + + +Create a plugin +================================================================== +You can create your own plugin to process the elevation map and publish as a layer in GridMap message. + +Let's look at the example. + +First, create your plugin file in `elevation_mapping_cupy/script/plugins/` and save as `example.py`. + +.. code-block:: python + + import cupy as cp + from typing import List + from .plugin_manager import PluginBase + + + class NameOfYourPlugin(PluginBase): + def __init__(self, add_value:float=1.0, **kwargs): + super().__init__() + self.add_value = float(add_value) + + def __call__(self, + elevation_map: cp.ndarray, + layer_names: List[str], + plugin_layers: cp.ndarray, + plugin_layer_names: List[str], + semantic_layers: cp.ndarray, + semantic_layer_names: List[str], + *args + )->cp.ndarray: + # Process maps here + # You can also use the other plugin's data through plugin_layers. + new_elevation = elevation_map[0] + self.add_value + return new_elevation + +Then, add your plugin setting to `config/plugin_config.yaml` + +.. code-block:: yaml + + example: # Name of your filter + type: "example" # Specify the name of your plugin (the name of your file name). + enable: True # weather to load this plugin + fill_nan: True # Fill nans to invalid cells of elevation layer. + is_height_layer: True # If this is a height layer (such as elevation) or not (such as traversability) + layer_name: "example_layer" # The layer name. + extra_params: # This params are passed to the plugin class on initialization. + add_value: 2.0 # Example param + + example_large: # You can apply same filter with different name. + type: "example" # Specify the name of your plugin (the name of your file name). + enable: True # weather to load this plugin + fill_nan: True # Fill nans to invalid cells of elevation layer. + is_height_layer: True # If this is a height layer (such as elevation) or not (such as traversability) + layer_name: "example_layer_large" # The layer name. + extra_params: # This params are passed to the plugin class on initialization. + add_value: 100.0 # Example param with larger value. + + +Finally, add your layer name to publishers in your config. You can create a new topic or add to existing topics. + +.. code-block:: yaml + + plugin_example: # Topic name + layers: [ 'elevation', 'example_layer', 'example_layer_large' ] + basic_layers: [ 'example_layer' ] + fps: 1.0 # The plugin is called with this fps. + + + + + +Existing plugins +================================================================== + +This section lists the plugins that are already installed and available for use. + + + + +1. Min filter +------------------------------------------------------------------- +.. automodule:: elevation_mapping_cupy.plugins.min_filter + :members: + +2. Inpainting +------------------------------------------------------------------- + +.. automodule:: elevation_mapping_cupy.plugins.inpainting + :members: + +3. Smooth Filter +------------------------------------------------------------------- +.. automodule:: elevation_mapping_cupy.plugins.smooth_filter + :members: + +4. Robot centric elevation +------------------------------------------------------------------- +.. automodule:: elevation_mapping_cupy.plugins.robot_centric_elevation + :members: + +5. Semantic Filter +------------------------------------------------------------------- +.. automodule:: elevation_mapping_cupy.plugins.semantic_filter + :members: + +6. Semantic traversability +------------------------------------------------------------------- +.. automodule:: elevation_mapping_cupy.plugins.semantic_traversability + :members: + +7. Features PCA +------------------------------------------------------------------- +.. automodule:: elevation_mapping_cupy.plugins.features_pca + :members: \ No newline at end of file diff --git a/_sources/usage/semantics.rst.txt b/_sources/usage/semantics.rst.txt new file mode 100644 index 00000000..24616a10 --- /dev/null +++ b/_sources/usage/semantics.rst.txt @@ -0,0 +1,79 @@ +.. _semantics: + +Semantics +****************************************************************** + +The elevation map is also able to include semantic information. +The workflow consists in two elements: + +* semantic extension of the elevation map +* semantic pointcloud + +semantic extension of the elevation map +========================================== + +The semantics of the elevation map can be configured in the sensor parameter file. +The sensor parameter file contains all the topics the map subscribes to. + +The channels and fusion lists are the parameters that define the semantics of the elevation map. +The channel is a list that contains the name of the semantic layers as well as the name of the channel +of the data that the elevation map node subscribes to. +The fusion list indicates the fusion algorithm type which is applied to the data to fuse the +sensor data into the map. + +There are different fusion algorithms types: + +* average +"""""""""""""""""""""""""" + + Takes the average of all the points that fall within the same cell and average them + and then takes a weighted average of the existing value. + + use case: semantic features + +* bayesian_inference: +"""""""""""""""""""""""""" + + Employs a gaussian bayesian inference at each iteration. Where we use the psoterior + of the previous iteration as the prior to the new iteration. + + use case: semantic features + + +* class_average +"""""""""""""""""""""""""" + + Takes the average of all the points that fall within the same cell and average them + and then takes a weighted average of the existing value. If the previous value is zero + it weights the previous value with a zero weight. + + use case: class probabilities + +* class_bayesian +"""""""""""""""""""""""""" + + Employs a bayesian inference of a categorical distribution with a dirichlet prior. + The alpha hyperparameters of the dirichlet prior are updated at every iteration, + such that the posterior of iteration t-1 is the prior of t. + + use case: class probabilities + + +* color +"""""""""""""""""""""""""" + + The color is subscribed as a uint32. The color of the cell is the result of the average of + all the points within that cell. + + use case: rgb color information + +Semantic pointcloud +======================================= + +Sensors do not always directly provide all semantic information. +The semantic pointcloud is a ROS node that subscribes to stereo cameras and generates a +multichannel pointcloud containing semantic information additionally to the goemteric position of +the points. +The pointcloud is also configured from the sensor_parameter file. + + diff --git a/_static/basic.css b/_static/basic.css new file mode 100644 index 00000000..f316efcb --- /dev/null +++ b/_static/basic.css @@ -0,0 +1,925 @@ +/* + * basic.css + * ~~~~~~~~~ + * + * Sphinx stylesheet -- basic theme. + * + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. + * :license: BSD, see LICENSE for details. + * + */ + +/* -- main layout ----------------------------------------------------------- */ + +div.clearer { + clear: both; +} + +div.section::after { + display: block; 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+ display: flex; + top: .3em; + right: .3em; + width: 1.7em; + height: 1.7em; + opacity: 0; + transition: opacity 0.3s, border .3s, background-color .3s; + user-select: none; + padding: 0; + border: none; + outline: none; + border-radius: 0.4em; + /* The colors that GitHub uses */ + border: #1b1f2426 1px solid; + background-color: #f6f8fa; + color: #57606a; +} + +button.copybtn.success { + border-color: #22863a; + color: #22863a; +} + +button.copybtn svg { + stroke: currentColor; + width: 1.5em; + height: 1.5em; + padding: 0.1em; +} + +div.highlight { + position: relative; +} + +/* Show the copybutton */ +.highlight:hover button.copybtn, button.copybtn.success { + opacity: 1; +} + +.highlight button.copybtn:hover { + background-color: rgb(235, 235, 235); +} + +.highlight button.copybtn:active { + background-color: rgb(187, 187, 187); +} + +/** + * A minimal CSS-only tooltip copied from: + * https://codepen.io/mildrenben/pen/rVBrpK + * + * To use, write HTML like the following: + * + *

Short

+ */ + .o-tooltip--left { + position: relative; + } + + .o-tooltip--left:after { + opacity: 0; + visibility: hidden; + position: absolute; + content: attr(data-tooltip); + padding: .2em; + font-size: .8em; + left: -.2em; + background: grey; + color: white; + white-space: nowrap; + z-index: 2; + border-radius: 2px; + transform: translateX(-102%) translateY(0); + transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); +} + +.o-tooltip--left:hover:after { + display: block; + opacity: 1; + visibility: visible; + transform: translateX(-100%) translateY(0); + transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); + transition-delay: .5s; +} + +/* By default the copy button shouldn't show up when printing a page */ +@media print { + button.copybtn { + display: none; + } +} diff --git a/_static/copybutton.js b/_static/copybutton.js new file mode 100644 index 00000000..2ea7ff3e --- /dev/null +++ b/_static/copybutton.js @@ -0,0 +1,248 @@ +// Localization support +const messages = { + 'en': { + 'copy': 'Copy', + 'copy_to_clipboard': 'Copy to clipboard', + 'copy_success': 'Copied!', + 'copy_failure': 'Failed to copy', + }, + 'es' : { + 'copy': 'Copiar', + 'copy_to_clipboard': 'Copiar al portapapeles', + 'copy_success': '¡Copiado!', + 'copy_failure': 'Error al copiar', + }, + 'de' : { + 'copy': 'Kopieren', + 'copy_to_clipboard': 'In die Zwischenablage kopieren', + 'copy_success': 'Kopiert!', + 'copy_failure': 'Fehler beim Kopieren', + }, + 'fr' : { + 'copy': 'Copier', + 'copy_to_clipboard': 'Copier dans le presse-papier', + 'copy_success': 'Copié !', + 'copy_failure': 'Échec de la copie', + }, + 'ru': { + 'copy': 'Скопировать', + 'copy_to_clipboard': 'Скопировать в буфер', + 'copy_success': 'Скопировано!', + 'copy_failure': 'Не удалось скопировать', + }, + 'zh-CN': { + 'copy': '复制', + 'copy_to_clipboard': '复制到剪贴板', + 'copy_success': '复制成功!', + 'copy_failure': '复制失败', + }, + 'it' : { + 'copy': 'Copiare', + 'copy_to_clipboard': 'Copiato negli appunti', + 'copy_success': 'Copiato!', + 'copy_failure': 'Errore durante la copia', + } +} + +let locale = 'en' +if( document.documentElement.lang !== undefined + && messages[document.documentElement.lang] !== undefined ) { + locale = document.documentElement.lang +} + +let doc_url_root = DOCUMENTATION_OPTIONS.URL_ROOT; +if (doc_url_root == '#') { + doc_url_root = ''; +} + +/** + * SVG files for our copy buttons + */ +let iconCheck = ` + ${messages[locale]['copy_success']} + + +` + +// If the user specified their own SVG use that, otherwise use the default +let iconCopy = ``; +if (!iconCopy) { + iconCopy = ` + ${messages[locale]['copy_to_clipboard']} + + + +` +} + +/** + * Set up copy/paste for code blocks + */ + +const runWhenDOMLoaded = cb => { + if (document.readyState != 'loading') { + cb() + } else if (document.addEventListener) { + document.addEventListener('DOMContentLoaded', cb) + } else { + document.attachEvent('onreadystatechange', function() { + if (document.readyState == 'complete') cb() + }) + } +} + +const codeCellId = index => `codecell${index}` + +// Clears selected text since ClipboardJS will select the text when copying +const clearSelection = () => { + if (window.getSelection) { + window.getSelection().removeAllRanges() + } else if (document.selection) { + document.selection.empty() + } +} + +// Changes tooltip text for a moment, then changes it back +// We want the timeout of our `success` class to be a bit shorter than the +// tooltip and icon change, so that we can hide the icon before changing back. +var timeoutIcon = 2000; +var timeoutSuccessClass = 1500; + +const temporarilyChangeTooltip = (el, oldText, newText) => { + el.setAttribute('data-tooltip', newText) + el.classList.add('success') + // Remove success a little bit sooner than we change the tooltip + // So that we can use CSS to hide the copybutton first + setTimeout(() => el.classList.remove('success'), timeoutSuccessClass) + setTimeout(() => el.setAttribute('data-tooltip', oldText), timeoutIcon) +} + +// Changes the copy button icon for two seconds, then changes it back +const temporarilyChangeIcon = (el) => { + el.innerHTML = iconCheck; + setTimeout(() => {el.innerHTML = iconCopy}, timeoutIcon) +} + +const addCopyButtonToCodeCells = () => { + // If ClipboardJS hasn't loaded, wait a bit and try again. This + // happens because we load ClipboardJS asynchronously. + if (window.ClipboardJS === undefined) { + setTimeout(addCopyButtonToCodeCells, 250) + return + } + + // Add copybuttons to all of our code cells + const COPYBUTTON_SELECTOR = 'div.highlight pre'; + const codeCells = document.querySelectorAll(COPYBUTTON_SELECTOR) + codeCells.forEach((codeCell, index) => { + const id = codeCellId(index) + codeCell.setAttribute('id', id) + + const clipboardButton = id => + `` + codeCell.insertAdjacentHTML('afterend', clipboardButton(id)) + }) + +function escapeRegExp(string) { + return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string +} + +/** + * Removes excluded text from a Node. + * + * @param {Node} target Node to filter. + * @param {string} exclude CSS selector of nodes to exclude. + * @returns {DOMString} Text from `target` with text removed. + */ +function filterText(target, exclude) { + const clone = target.cloneNode(true); // clone as to not modify the live DOM + if (exclude) { + // remove excluded nodes + clone.querySelectorAll(exclude).forEach(node => node.remove()); + } + return clone.innerText; +} + +// Callback when a copy button is clicked. Will be passed the node that was clicked +// should then grab the text and replace pieces of text that shouldn't be used in output +function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { + var regexp; + var match; + + // Do we check for line continuation characters and "HERE-documents"? + var useLineCont = !!lineContinuationChar + var useHereDoc = !!hereDocDelim + + // create regexp to capture prompt and remaining line + if (isRegexp) { + regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') + } else { + regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') + } + + const outputLines = []; + var promptFound = false; + var gotLineCont = false; + var gotHereDoc = false; + const lineGotPrompt = []; + for (const line of textContent.split('\n')) { + match = line.match(regexp) + if (match || gotLineCont || gotHereDoc) { + promptFound = regexp.test(line) + lineGotPrompt.push(promptFound) + if (removePrompts && promptFound) { + outputLines.push(match[2]) + } else { + outputLines.push(line) + } + gotLineCont = line.endsWith(lineContinuationChar) & useLineCont + if (line.includes(hereDocDelim) & useHereDoc) + gotHereDoc = !gotHereDoc + } else if (!onlyCopyPromptLines) { + outputLines.push(line) + } else if (copyEmptyLines && line.trim() === '') { + outputLines.push(line) + } + } + + // If no lines with the prompt were found then just use original lines + if (lineGotPrompt.some(v => v === true)) { + textContent = outputLines.join('\n'); + } + + // Remove a trailing newline to avoid auto-running when pasting + if (textContent.endsWith("\n")) { + textContent = textContent.slice(0, -1) + } + return textContent +} + + +var copyTargetText = (trigger) => { + var target = document.querySelector(trigger.attributes['data-clipboard-target'].value); + + // get filtered text + let exclude = '.linenos'; + + let text = filterText(target, exclude); + return formatCopyText(text, '', false, true, true, true, '', '') +} + + // Initialize with a callback so we can modify the text before copy + const clipboard = new ClipboardJS('.copybtn', {text: copyTargetText}) + + // Update UI with error/success messages + clipboard.on('success', event => { + clearSelection() + temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_success']) + temporarilyChangeIcon(event.trigger) + }) + + clipboard.on('error', event => { + temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_failure']) + }) +} + +runWhenDOMLoaded(addCopyButtonToCodeCells) \ No newline at end of file diff --git a/_static/copybutton_funcs.js b/_static/copybutton_funcs.js new file mode 100644 index 00000000..dbe1aaad --- /dev/null +++ b/_static/copybutton_funcs.js @@ -0,0 +1,73 @@ +function escapeRegExp(string) { + return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string +} + +/** + * Removes excluded text from a Node. + * + * @param {Node} target Node to filter. + * @param {string} exclude CSS selector of nodes to exclude. + * @returns {DOMString} Text from `target` with text removed. + */ +export function filterText(target, exclude) { + const clone = target.cloneNode(true); // clone as to not modify the live DOM + if (exclude) { + // remove excluded nodes + clone.querySelectorAll(exclude).forEach(node => node.remove()); + } + return clone.innerText; +} + +// Callback when a copy button is clicked. Will be passed the node that was clicked +// should then grab the text and replace pieces of text that shouldn't be used in output +export function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { + var regexp; + var match; + + // Do we check for line continuation characters and "HERE-documents"? + var useLineCont = !!lineContinuationChar + var useHereDoc = !!hereDocDelim + + // create regexp to capture prompt and remaining line + if (isRegexp) { + regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') + } else { + regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') + } + + const outputLines = []; + var promptFound = false; + var gotLineCont = false; + var gotHereDoc = false; + const lineGotPrompt = []; + for (const line of textContent.split('\n')) { + match = line.match(regexp) + if (match || gotLineCont || gotHereDoc) { + promptFound = regexp.test(line) + lineGotPrompt.push(promptFound) + if (removePrompts && promptFound) { + outputLines.push(match[2]) + } else { + outputLines.push(line) + } + gotLineCont = line.endsWith(lineContinuationChar) & useLineCont + if (line.includes(hereDocDelim) & useHereDoc) + gotHereDoc = !gotHereDoc + } else if (!onlyCopyPromptLines) { + outputLines.push(line) + } else if (copyEmptyLines && line.trim() === '') { + outputLines.push(line) + } + } + + // If no lines with the prompt were found then just use original lines + if (lineGotPrompt.some(v => v === true)) { + textContent = outputLines.join('\n'); + } + + // Remove a trailing newline to avoid auto-running when pasting + if (textContent.endsWith("\n")) { + textContent = textContent.slice(0, -1) + } + return textContent +} diff --git a/_static/css/badge_only.css b/_static/css/badge_only.css new file mode 100644 index 00000000..c718cee4 --- /dev/null +++ b/_static/css/badge_only.css @@ -0,0 +1 @@ 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// [C]VC[V] is m=1 + var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1 + var s_v = "^(" + C + ")?" + v; // vowel in stem + + this.stemWord = function (w) { + var stem; + var suffix; + var firstch; + var origword = w; + + if (w.length < 3) + return w; + + var re; + var re2; + var re3; + var re4; + + firstch = w.substr(0,1); + if (firstch == "y") + w = firstch.toUpperCase() + w.substr(1); + + // Step 1a + re = /^(.+?)(ss|i)es$/; + re2 = /^(.+?)([^s])s$/; + + if (re.test(w)) + w = w.replace(re,"$1$2"); + else if (re2.test(w)) + w = w.replace(re2,"$1$2"); + + // Step 1b + re = /^(.+?)eed$/; + re2 = /^(.+?)(ed|ing)$/; + if (re.test(w)) { + var fp = re.exec(w); + re = new RegExp(mgr0); + if (re.test(fp[1])) { + re = /.$/; + w = w.replace(re,""); + } + } + else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1]; + re2 = new RegExp(s_v); + if (re2.test(stem)) { + w = stem; + re2 = /(at|bl|iz)$/; + re3 = new RegExp("([^aeiouylsz])\\1$"); + re4 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + if (re2.test(w)) + w = w + "e"; + else if (re3.test(w)) { + re = /.$/; + w = w.replace(re,""); + } + else if (re4.test(w)) + w = w + "e"; + } + } + + // Step 1c + re = /^(.+?)y$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(s_v); + if (re.test(stem)) + w = stem + "i"; + } + + // Step 2 + re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step2list[suffix]; + } + + // Step 3 + re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step3list[suffix]; + } + + // Step 4 + re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; + re2 = /^(.+?)(s|t)(ion)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(mgr1); + if (re.test(stem)) + w = stem; + } + else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1] + fp[2]; + re2 = new RegExp(mgr1); + if (re2.test(stem)) + w = stem; + } + + // Step 5 + re = /^(.+?)e$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(mgr1); + re2 = new RegExp(meq1); + re3 = new RegExp("^" + C + v + "[^aeiouwxy]$"); + if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) + w = stem; + } + re = /ll$/; + re2 = new RegExp(mgr1); + if (re.test(w) && re2.test(w)) { + re = /.$/; + w = w.replace(re,""); + } + + // and turn initial Y back to y + if (firstch == "y") + w = firstch.toLowerCase() + w.substr(1); + return w; + } +} + diff --git a/_static/minus.png b/_static/minus.png new file mode 100644 index 00000000..d96755fd Binary files /dev/null and b/_static/minus.png differ diff --git a/_static/plus.png b/_static/plus.png new file mode 100644 index 00000000..7107cec9 Binary files /dev/null and b/_static/plus.png differ diff --git a/_static/pygments.css b/_static/pygments.css new file mode 100644 index 00000000..84ab3030 --- /dev/null +++ b/_static/pygments.css @@ -0,0 +1,75 @@ +pre { line-height: 125%; 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+ +/** + * Simple result scoring code. + */ +if (typeof Scorer === "undefined") { + var Scorer = { + // Implement the following function to further tweak the score for each result + // The function takes a result array [docname, title, anchor, descr, score, filename] + // and returns the new score. + /* + score: result => { + const [docname, title, anchor, descr, score, filename] = result + return score + }, + */ + + // query matches the full name of an object + objNameMatch: 11, + // or matches in the last dotted part of the object name + objPartialMatch: 6, + // Additive scores depending on the priority of the object + objPrio: { + 0: 15, // used to be importantResults + 1: 5, // used to be objectResults + 2: -5, // used to be unimportantResults + }, + // Used when the priority is not in the mapping. + objPrioDefault: 0, + + // query found in title + title: 15, + partialTitle: 7, + // query found in terms + term: 5, + partialTerm: 2, + }; +} + +const _removeChildren = (element) => { + while (element && element.lastChild) element.removeChild(element.lastChild); +}; + +/** + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping + */ +const _escapeRegExp = (string) => + string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string + +const _displayItem = (item, searchTerms, highlightTerms) => { + const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; + const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; + const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; + const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; + const contentRoot = document.documentElement.dataset.content_root; + + const [docName, title, anchor, descr, score, _filename] = item; + + let listItem = document.createElement("li"); + let requestUrl; + let linkUrl; + if (docBuilder === "dirhtml") { + // dirhtml builder + let dirname = docName + "/"; + if (dirname.match(/\/index\/$/)) + dirname = dirname.substring(0, dirname.length - 6); + else if (dirname === "index/") dirname = ""; + requestUrl = contentRoot + dirname; + linkUrl = requestUrl; + } else { + // normal html builders + requestUrl = contentRoot + docName + docFileSuffix; + linkUrl = docName + docLinkSuffix; + } + let linkEl = listItem.appendChild(document.createElement("a")); + linkEl.href = linkUrl + anchor; + linkEl.dataset.score = score; + linkEl.innerHTML = title; + if (descr) { + listItem.appendChild(document.createElement("span")).innerHTML = + " (" + descr + ")"; + // highlight search terms in the description + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + } + else if (showSearchSummary) + fetch(requestUrl) + .then((responseData) => responseData.text()) + .then((data) => { + if (data) + listItem.appendChild( + Search.makeSearchSummary(data, searchTerms, anchor) + ); + // highlight search terms in the summary + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + }); + Search.output.appendChild(listItem); +}; +const _finishSearch = (resultCount) => { + Search.stopPulse(); + Search.title.innerText = _("Search Results"); + if (!resultCount) + Search.status.innerText = Documentation.gettext( + "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories." + ); + else + Search.status.innerText = _( + "Search finished, found ${resultCount} page(s) matching the search query." + ).replace('${resultCount}', resultCount); +}; +const _displayNextItem = ( + results, + resultCount, + searchTerms, + highlightTerms, +) => { + // results left, load the summary and display it + // this is intended to be dynamic (don't sub resultsCount) + if (results.length) { + _displayItem(results.pop(), searchTerms, highlightTerms); + setTimeout( + () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), + 5 + ); + } + // search finished, update title and status message + else _finishSearch(resultCount); +}; +// Helper function used by query() to order search results. +// Each input is an array of [docname, title, anchor, descr, score, filename]. +// Order the results by score (in opposite order of appearance, since the +// `_displayNextItem` function uses pop() to retrieve items) and then alphabetically. +const _orderResultsByScoreThenName = (a, b) => { + const leftScore = a[4]; + const rightScore = b[4]; + if (leftScore === rightScore) { + // same score: sort alphabetically + const leftTitle = a[1].toLowerCase(); + const rightTitle = b[1].toLowerCase(); + if (leftTitle === rightTitle) return 0; + return leftTitle > rightTitle ? -1 : 1; // inverted is intentional + } + return leftScore > rightScore ? 1 : -1; +}; + +/** + * Default splitQuery function. Can be overridden in ``sphinx.search`` with a + * custom function per language. + * + * The regular expression works by splitting the string on consecutive characters + * that are not Unicode letters, numbers, underscores, or emoji characters. + * This is the same as ``\W+`` in Python, preserving the surrogate pair area. + */ +if (typeof splitQuery === "undefined") { + var splitQuery = (query) => query + .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) + .filter(term => term) // remove remaining empty strings +} + +/** + * Search Module + */ +const Search = { + _index: null, + _queued_query: null, + _pulse_status: -1, + + htmlToText: (htmlString, anchor) => { + const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html'); + for (const removalQuery of [".headerlinks", "script", "style"]) { + htmlElement.querySelectorAll(removalQuery).forEach((el) => { el.remove() }); + } + if (anchor) { + const anchorContent = htmlElement.querySelector(`[role="main"] ${anchor}`); + if (anchorContent) return anchorContent.textContent; + + console.warn( + `Anchored content block not found. Sphinx search tries to obtain it via DOM query '[role=main] ${anchor}'. Check your theme or template.` + ); + } + + // if anchor not specified or not found, fall back to main content + const docContent = htmlElement.querySelector('[role="main"]'); + if (docContent) return docContent.textContent; + + console.warn( + "Content block not found. Sphinx search tries to obtain it via DOM query '[role=main]'. Check your theme or template." + ); + return ""; + }, + + init: () => { + const query = new URLSearchParams(window.location.search).get("q"); + document + .querySelectorAll('input[name="q"]') + .forEach((el) => (el.value = query)); + if (query) Search.performSearch(query); + }, + + loadIndex: (url) => + (document.body.appendChild(document.createElement("script")).src = url), + + setIndex: (index) => { + Search._index = index; + if (Search._queued_query !== null) { + const query = Search._queued_query; + Search._queued_query = null; + Search.query(query); + } + }, + + hasIndex: () => Search._index !== null, + + deferQuery: (query) => (Search._queued_query = query), + + stopPulse: () => (Search._pulse_status = -1), + + startPulse: () => { + if (Search._pulse_status >= 0) return; + + const pulse = () => { + Search._pulse_status = (Search._pulse_status + 1) % 4; + Search.dots.innerText = ".".repeat(Search._pulse_status); + if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); + }; + pulse(); + }, + + /** + * perform a search for something (or wait until index is loaded) + */ + performSearch: (query) => { + // create the required interface elements + const searchText = document.createElement("h2"); + searchText.textContent = _("Searching"); + const searchSummary = document.createElement("p"); + searchSummary.classList.add("search-summary"); + searchSummary.innerText = ""; + const searchList = document.createElement("ul"); + searchList.classList.add("search"); + + const out = document.getElementById("search-results"); + Search.title = out.appendChild(searchText); + Search.dots = Search.title.appendChild(document.createElement("span")); + Search.status = out.appendChild(searchSummary); + Search.output = out.appendChild(searchList); + + const searchProgress = document.getElementById("search-progress"); + // Some themes don't use the search progress node + if (searchProgress) { + searchProgress.innerText = _("Preparing search..."); + } + Search.startPulse(); + + // index already loaded, the browser was quick! + if (Search.hasIndex()) Search.query(query); + else Search.deferQuery(query); + }, + + _parseQuery: (query) => { + // stem the search terms and add them to the correct list + const stemmer = new Stemmer(); + const searchTerms = new Set(); + const excludedTerms = new Set(); + const highlightTerms = new Set(); + const objectTerms = new Set(splitQuery(query.toLowerCase().trim())); + splitQuery(query.trim()).forEach((queryTerm) => { + const queryTermLower = queryTerm.toLowerCase(); + + // maybe skip this "word" + // stopwords array is from language_data.js + if ( + stopwords.indexOf(queryTermLower) !== -1 || + queryTerm.match(/^\d+$/) + ) + return; + + // stem the word + let word = stemmer.stemWord(queryTermLower); + // select the correct list + if (word[0] === "-") excludedTerms.add(word.substr(1)); + else { + searchTerms.add(word); + highlightTerms.add(queryTermLower); + } + }); + + if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js + localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" ")) + } + + // console.debug("SEARCH: searching for:"); + // console.info("required: ", [...searchTerms]); + // console.info("excluded: ", [...excludedTerms]); + + return [query, searchTerms, excludedTerms, highlightTerms, objectTerms]; + }, + + /** + * execute search (requires search index to be loaded) + */ + _performSearch: (query, searchTerms, excludedTerms, highlightTerms, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + const allTitles = Search._index.alltitles; + const indexEntries = Search._index.indexentries; + + // Collect multiple result groups to be sorted separately and then ordered. + // Each is an array of [docname, title, anchor, descr, score, filename]. + const normalResults = []; + const nonMainIndexResults = []; + + _removeChildren(document.getElementById("search-progress")); + + const queryLower = query.toLowerCase().trim(); + for (const [title, foundTitles] of Object.entries(allTitles)) { + if (title.toLowerCase().trim().includes(queryLower) && (queryLower.length >= title.length/2)) { + for (const [file, id] of foundTitles) { + let score = Math.round(100 * queryLower.length / title.length) + normalResults.push([ + docNames[file], + titles[file] !== title ? `${titles[file]} > ${title}` : title, + id !== null ? "#" + id : "", + null, + score, + filenames[file], + ]); + } + } + } + + // search for explicit entries in index directives + for (const [entry, foundEntries] of Object.entries(indexEntries)) { + if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { + for (const [file, id, isMain] of foundEntries) { + const score = Math.round(100 * queryLower.length / entry.length); + const result = [ + docNames[file], + titles[file], + id ? "#" + id : "", + null, + score, + filenames[file], + ]; + if (isMain) { + normalResults.push(result); + } else { + nonMainIndexResults.push(result); + } + } + } + } + + // lookup as object + objectTerms.forEach((term) => + normalResults.push(...Search.performObjectSearch(term, objectTerms)) + ); + + // lookup as search terms in fulltext + normalResults.push(...Search.performTermsSearch(searchTerms, excludedTerms)); + + // let the scorer override scores with a custom scoring function + if (Scorer.score) { + normalResults.forEach((item) => (item[4] = Scorer.score(item))); + nonMainIndexResults.forEach((item) => (item[4] = Scorer.score(item))); + } + + // Sort each group of results by score and then alphabetically by name. + normalResults.sort(_orderResultsByScoreThenName); + nonMainIndexResults.sort(_orderResultsByScoreThenName); + + // Combine the result groups in (reverse) order. + // Non-main index entries are typically arbitrary cross-references, + // so display them after other results. + let results = [...nonMainIndexResults, ...normalResults]; + + // remove duplicate search results + // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept + let seen = new Set(); + results = results.reverse().reduce((acc, result) => { + let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(','); + if (!seen.has(resultStr)) { + acc.push(result); + seen.add(resultStr); + } + return acc; + }, []); + + return results.reverse(); + }, + + query: (query) => { + const [searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms] = Search._parseQuery(query); + const results = Search._performSearch(searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms); + + // for debugging + //Search.lastresults = results.slice(); // a copy + // console.info("search results:", Search.lastresults); + + // print the results + _displayNextItem(results, results.length, searchTerms, highlightTerms); + }, + + /** + * search for object names + */ + performObjectSearch: (object, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const objects = Search._index.objects; + const objNames = Search._index.objnames; + const titles = Search._index.titles; + + const results = []; + + const objectSearchCallback = (prefix, match) => { + const name = match[4] + const fullname = (prefix ? prefix + "." : "") + name; + const fullnameLower = fullname.toLowerCase(); + if (fullnameLower.indexOf(object) < 0) return; + + let score = 0; + const parts = fullnameLower.split("."); + + // check for different match types: exact matches of full name or + // "last name" (i.e. last dotted part) + if (fullnameLower === object || parts.slice(-1)[0] === object) + score += Scorer.objNameMatch; + else if (parts.slice(-1)[0].indexOf(object) > -1) + score += Scorer.objPartialMatch; // matches in last name + + const objName = objNames[match[1]][2]; + const title = titles[match[0]]; + + // If more than one term searched for, we require other words to be + // found in the name/title/description + const otherTerms = new Set(objectTerms); + otherTerms.delete(object); + if (otherTerms.size > 0) { + const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase(); + if ( + [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0) + ) + return; + } + + let anchor = match[3]; + if (anchor === "") anchor = fullname; + else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname; + + const descr = objName + _(", in ") + title; + + // add custom score for some objects according to scorer + if (Scorer.objPrio.hasOwnProperty(match[2])) + score += Scorer.objPrio[match[2]]; + else score += Scorer.objPrioDefault; + + results.push([ + docNames[match[0]], + fullname, + "#" + anchor, + descr, + score, + filenames[match[0]], + ]); + }; + Object.keys(objects).forEach((prefix) => + objects[prefix].forEach((array) => + objectSearchCallback(prefix, array) + ) + ); + return results; + }, + + /** + * search for full-text terms in the index + */ + performTermsSearch: (searchTerms, excludedTerms) => { + // prepare search + const terms = Search._index.terms; + const titleTerms = Search._index.titleterms; + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + + const scoreMap = new Map(); + const fileMap = new Map(); + + // perform the search on the required terms + searchTerms.forEach((word) => { + const files = []; + const arr = [ + { files: terms[word], score: Scorer.term }, + { files: titleTerms[word], score: Scorer.title }, + ]; + // add support for partial matches + if (word.length > 2) { + const escapedWord = _escapeRegExp(word); + if (!terms.hasOwnProperty(word)) { + Object.keys(terms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: terms[term], score: Scorer.partialTerm }); + }); + } + if (!titleTerms.hasOwnProperty(word)) { + Object.keys(titleTerms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: titleTerms[term], score: Scorer.partialTitle }); + }); + } + } + + // no match but word was a required one + if (arr.every((record) => record.files === undefined)) return; + + // found search word in contents + arr.forEach((record) => { + if (record.files === undefined) return; + + let recordFiles = record.files; + if (recordFiles.length === undefined) recordFiles = [recordFiles]; + files.push(...recordFiles); + + // set score for the word in each file + recordFiles.forEach((file) => { + if (!scoreMap.has(file)) scoreMap.set(file, {}); + scoreMap.get(file)[word] = record.score; + }); + }); + + // create the mapping + files.forEach((file) => { + if (!fileMap.has(file)) fileMap.set(file, [word]); + else if (fileMap.get(file).indexOf(word) === -1) fileMap.get(file).push(word); + }); + }); + + // now check if the files don't contain excluded terms + const results = []; + for (const [file, wordList] of fileMap) { + // check if all requirements are matched + + // as search terms with length < 3 are discarded + const filteredTermCount = [...searchTerms].filter( + (term) => term.length > 2 + ).length; + if ( + wordList.length !== searchTerms.size && + wordList.length !== filteredTermCount + ) + continue; + + // ensure that none of the excluded terms is in the search result + if ( + [...excludedTerms].some( + (term) => + terms[term] === file || + titleTerms[term] === file || + (terms[term] || []).includes(file) || + (titleTerms[term] || []).includes(file) + ) + ) + break; + + // select one (max) score for the file. + const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w])); + // add result to the result list + results.push([ + docNames[file], + titles[file], + "", + null, + score, + filenames[file], + ]); + } + return results; + }, + + /** + * helper function to return a node containing the + * search summary for a given text. keywords is a list + * of stemmed words. + */ + makeSearchSummary: (htmlText, keywords, anchor) => { + const text = Search.htmlToText(htmlText, anchor); + if (text === "") return null; + + const textLower = text.toLowerCase(); + const actualStartPosition = [...keywords] + .map((k) => textLower.indexOf(k.toLowerCase())) + .filter((i) => i > -1) + .slice(-1)[0]; + const startWithContext = Math.max(actualStartPosition - 120, 0); + + const top = startWithContext === 0 ? "" : "..."; + const tail = startWithContext + 240 < text.length ? "..." : ""; + + let summary = document.createElement("p"); + summary.classList.add("context"); + summary.textContent = top + text.substr(startWithContext, 240).trim() + tail; + + return summary; + }, +}; + +_ready(Search.init); diff --git a/_static/sphinx_highlight.js b/_static/sphinx_highlight.js new file mode 100644 index 00000000..8a96c69a --- /dev/null +++ b/_static/sphinx_highlight.js @@ -0,0 +1,154 @@ +/* Highlighting utilities for Sphinx HTML documentation. */ +"use strict"; + +const SPHINX_HIGHLIGHT_ENABLED = true + +/** + * highlight a given string on a node by wrapping it in + * span elements with the given class name. + */ +const _highlight = (node, addItems, text, className) => { + if (node.nodeType === Node.TEXT_NODE) { + const val = node.nodeValue; + const parent = node.parentNode; + const pos = val.toLowerCase().indexOf(text); + if ( + pos >= 0 && + !parent.classList.contains(className) && + !parent.classList.contains("nohighlight") + ) { + let span; + + const closestNode = parent.closest("body, svg, foreignObject"); + const isInSVG = closestNode && closestNode.matches("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.classList.add(className); + } + + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + const rest = document.createTextNode(val.substr(pos + text.length)); + parent.insertBefore( + span, + parent.insertBefore( + rest, + node.nextSibling + ) + ); + node.nodeValue = val.substr(0, pos); + /* There may be more occurrences of search term in this node. So call this + * function recursively on the remaining fragment. + */ + _highlight(rest, addItems, text, className); + + if (isInSVG) { + const rect = document.createElementNS( + "http://www.w3.org/2000/svg", + "rect" + ); + const bbox = parent.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute("class", className); + addItems.push({ parent: parent, target: rect }); + } + } + } else if (node.matches && !node.matches("button, select, textarea")) { + node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); + } +}; +const _highlightText = (thisNode, text, className) => { + let addItems = []; + _highlight(thisNode, addItems, text, className); + addItems.forEach((obj) => + obj.parent.insertAdjacentElement("beforebegin", obj.target) + ); +}; + +/** + * Small JavaScript module for the documentation. + */ +const SphinxHighlight = { + + /** + * highlight the search words provided in localstorage in the text + */ + highlightSearchWords: () => { + if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight + + // get and clear terms from localstorage + const url = new URL(window.location); + const highlight = + localStorage.getItem("sphinx_highlight_terms") + || url.searchParams.get("highlight") + || ""; + localStorage.removeItem("sphinx_highlight_terms") + url.searchParams.delete("highlight"); + window.history.replaceState({}, "", url); + + // get individual terms from highlight string + const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); + if (terms.length === 0) return; // nothing to do + + // There should never be more than one element matching "div.body" + const divBody = document.querySelectorAll("div.body"); + const body = divBody.length ? divBody[0] : document.querySelector("body"); + window.setTimeout(() => { + terms.forEach((term) => _highlightText(body, term, "highlighted")); + }, 10); + + const searchBox = document.getElementById("searchbox"); + if (searchBox === null) return; + searchBox.appendChild( + document + .createRange() + .createContextualFragment( + '

' + + '' + + _("Hide Search Matches") + + "

" + ) + ); + }, + + /** + * helper function to hide the search marks again + */ + hideSearchWords: () => { + document + .querySelectorAll("#searchbox .highlight-link") + .forEach((el) => el.remove()); + document + .querySelectorAll("span.highlighted") + .forEach((el) => el.classList.remove("highlighted")); + localStorage.removeItem("sphinx_highlight_terms") + }, + + initEscapeListener: () => { + // only install a listener if it is really needed + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; + // bail with special keys + if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; + if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { + SphinxHighlight.hideSearchWords(); + event.preventDefault(); + } + }); + }, +}; + +_ready(() => { + /* Do not call highlightSearchWords() when we are on the search page. + * It will highlight words from the *previous* search query. + */ + if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); + SphinxHighlight.initEscapeListener(); +}); diff --git a/documentation.html b/documentation.html new file mode 100644 index 00000000..f1baea15 --- /dev/null +++ b/documentation.html @@ -0,0 +1,170 @@ + + + + + + + Multi-modal elevation mapping’s documentation — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Multi-modal elevation mapping’s documentation

+

Welcome to elevation mapping documentation

+python tests +documentation +
+

Index

+
+
Introduction - What is elevation mapping cupy
+
Installation - How to install the elevation map
+
Tutorial - How to launch the first elevation map
+
+

This is a ROS package for elevation mapping on GPU. The elevation mapping code is written in python and uses cupy for GPU computation. The +plane segmentation is done independently and runs on CPU. When the plane segmentation is generated, local convex approximations of the +terrain can be efficiently generated.

+Elevation map examples +Overview of the project +
+
+

Citing

+

If you use the elevation mapping cupy, please cite the following paper: +Elevation Mapping for Locomotion and Navigation using GPU

+
+

Hint

+

Elevation Mapping for Locomotion and Navigation using GPU Link

+

Takahiro Miki, Lorenz Wellhausen, Ruben Grandia, Fabian Jenelten, Timon Homberger, Marco Hutter

+
+
@misc{mikielevation2022,
+    doi = {10.48550/ARXIV.2204.12876},
+    author = {Miki, Takahiro and Wellhausen, Lorenz and Grandia, Ruben and Jenelten, Fabian and Homberger, Timon and Hutter, Marco},
+    keywords = {Robotics (cs.RO), FOS: Computer and information sciences, FOS: Computer and information sciences},
+    title = {Elevation Mapping for Locomotion and Navigation using GPU},
+    publisher = {International Conference on Intelligent Robots and Systems (IROS)},
+    year = {2022},
+}
+
+
+

Multi-modal elevation mapping if you use color or semantic layers

+
+

Hint

+

MEM: Multi-Modal Elevation Mapping for Robotics and Learning Link

+

Gian Erni, Jonas Frey, Takahiro Miki, Matias Mattamala, Marco Hutter

+
+
@misc{Erni2023-bs,
+    title = "{MEM}: {Multi-Modal} Elevation Mapping for Robotics and Learning",
+    author = "Erni, Gian and Frey, Jonas and Miki, Takahiro and Mattamala, Matias and Hutter, Marco",
+    publisher = {International Conference on Intelligent Robots and Systems (IROS)},
+    year = {2023},
+}
+
+
+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2022, Takahiro Miki, Gian Erni.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/genindex.html b/genindex.html new file mode 100644 index 00000000..79c47eb9 --- /dev/null +++ b/genindex.html @@ -0,0 +1,931 @@ + + + + + + Index — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
    • +
  • Index
    • +
  • +
    • +
+
+
+
+
+ + +

Index

+ +
+ _ + | A + | C + | D + | E + | F + | G + | I + | L + | M + | N + | O + | P + | R + | S + | T + | U + | W + | X + +
+

_

+ + +
+ +

A

+ + + +
+ +

C

+ + + +
+ +

D

+ + + +
+ +

E

+ + + +
    +
  • + elevation_mapping_cupy.elevation_mapping + +
    • +
  • + elevation_mapping_cupy.fusion + +
    • +
  • + elevation_mapping_cupy.parameter + +
    • +
  • + elevation_mapping_cupy.plugins.features_pca + +
    • +
  • + elevation_mapping_cupy.plugins.min_filter + +
    • +
  • + elevation_mapping_cupy.plugins.plugin_manager + +
    • +
  • + elevation_mapping_cupy.plugins.robot_centric_elevation + +
    • +
+ +

F

+ + + +
+ +

G

+ + + +
+ +

I

+ + + +
+ +

L

+ + + +
+ +

M

+ + + +
+ +

N

+ + +
+ +

O

+ + + +
+ +

P

+ + + +
+ +

R

+ + + +
+ +

S

+ + + +
+ +

T

+ + + +
+ +

U

+ + + +
+ +

W

+ + + +
+ +

X

+ + +
+ + + +
+
+
+ +
+ +
+

© Copyright 2022, Takahiro Miki, Gian Erni.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/getting_started/cuda_installation.html b/getting_started/cuda_installation.html new file mode 100644 index 00000000..5eb16c20 --- /dev/null +++ b/getting_started/cuda_installation.html @@ -0,0 +1,149 @@ + + + + + + + Cuda installation — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Cuda installation

+
+

CUDA

+

You can download CUDA10.2 from here. +You can follow the instruction.

+
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
+
+sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
+
+sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
+
+sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ /"
+
+sudo apt-get update
+
+sudo apt-get -y install cuda
+
+
+
+
+

cuDNN

+

You can download specific version from here. +For example, the tested version is with libcudnn8_8.0.0.180-1+cuda10.2_amd64.deb.

+

Then install them using the command below.

+
sudo dpkg -i libcudnn8_8.0.0.180-1+cuda10.2_amd64.deb
+
+sudo dpkg -i libcudnn8-dev_8.0.0.180-1+cuda10.2_amd64.deb
+
+
+
+
+ + +
+
+
+ +
+ +
+

© Copyright 2022, Takahiro Miki, Gian Erni.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/getting_started/installation.html b/getting_started/installation.html new file mode 100644 index 00000000..e980f905 --- /dev/null +++ b/getting_started/installation.html @@ -0,0 +1,360 @@ + + + + + + + Installation — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Installation

+

This section provides instructions for installing the necessary dependencies for the project. The installation process includes setting up CUDA & cuDNN, installing Python dependencies, and configuring Cupy. +Follow the instructions carefully to avoid any installation issues.

+
+

Dockers

+

We provide a docker setup for the project. +To build the docker image, run the following command:

+
cd <project_root>/docker
+./build.sh
+
+
+

To run the docker image, run the following command:

+
cd <project_root>/docker
+./run.sh
+
+
+

This will start the docker container and mount the home directory of the host machine to the docker container. +After you clone the project repository into your catkin_ws, you can build the packages inside the docker container. +To build the packages inside the docker container, follow the instructions in the Build section of this document.

+
+
+

On Desktop or Laptop with NVIDIA GPU

+
+

CUDA & cuDNN

+

If you do not have CUDA and cuDNN installed, please install them first. +The tested versions are CUDA10.2, 11.6

+

CUDA +cuDNN

+

You can check how to install here.

+
+
+

Python dependencies

+

You will need

+ +

For traversability filter, either of

+ +

Optionally, OpenCV for inpainting filter.

+ +

Install numpy, scipy, shapely, opencv-python with the following command.

+
pip3 install -r requirements.txt
+
+
+
+
+

Cupy

+

cupy can be installed with specific CUDA versions. (On jetson, only “from source” i.e. pip install cupy could work) +For CUDA 10.2

+
pip install cupy-cuda102
+
+
+

For CUDA 11.0

+
pip install cupy-cuda110
+
+
+

For CUDA 11.1

+
pip install cupy-cuda111
+
+
+

For CUDA 11.2

+
pip install cupy-cuda112
+
+
+

For CUDA 11.3

+
pip install cupy-cuda113
+
+
+

For CUDA 11.4

+
pip install cupy-cuda114
+
+
+

For CUDA 11.5

+
pip install cupy-cuda115
+
+
+

For CUDA 11.6

+
pip install cupy-cuda116
+
+
+

(Install CuPy from source)

+
pip install cupy
+
+
+
+
+

Traversability filter

+

You can choose either pytorch, or chainer to run the CNN based traversability filter. +Install by following the official documents.

+ +

Pytorch uses ~2GB more GPU memory than Chainer, but runs a bit faster. +Use parameter use_chainer to select which backend to use.

+
+
+

ROS package dependencies

+ +
sudo apt install ros-noetic-pybind11-catkin
+sudo apt install ros-noetic-grid-map-core ros-noetic-grid-map-msgs
+
+
+
+
+
+

On Jetson

+
+

CUDA CuDNN

+

CUDA and cuDNN can be installed via apt. It comes with nvidia-jetpack. The tested version is jetpack 4.5 with L4T 32.5.0.

+
+
+

Python dependencies

+

On jetson, you need the version for its CPU arch:

+
wget https://nvidia.box.com/shared/static/p57jwntv436lfrd78inwl7iml6p13fzh.whl -O torch-1.8.0-cp36-cp36m-linux_aarch64.whl
+pip3 install Cython
+pip3 install numpy==1.19.5 torch-1.8.0-cp36-cp36m-linux_aarch64.whl
+
+
+

Also, you need to install cupy with

+
pip3 install cupy
+
+
+

This builds the packages from source so it would take time.

+
+
+

ROS dependencies

+ +
sudo apt install ros-melodic-pybind11-catkin
+sudo apt install ros-melodic-grid-map-core ros-melodic-grid-map-msgs
+
+
+

Also, on jetson you need fortran (should already be installed).

+
sudo apt install gfortran
+
+
+

If the Jetson is set up with Jetpack 4.5 with ROS Melodic the following package is additionally required:

+
git clone git@github.com:ros/filters.git -b noetic-devel
+
+
+
+
+
+

Plane segmentation dependencies

+
+

OpenCV

+
sudo apt install libopencv-dev
+
+
+
+
+

Eigen

+
sudo apt install libeigen3-dev
+
+
+
+
+

CGAL

+

CGAL5 is required. It will be automatically downloaded and installed into the catkin workspace by the cgal5_catkin package. Make sure you +have the third-party libaries installed on you machine:

+
sudo apt install libgmp-dev
+sudo apt install libmpfr-dev
+sudo apt install libboost-all-dev
+
+
+
+
+
+

Semantic Sensors

+

Elevation mapping node can receive multi-modal point cloud and image topics. +In this example, we use semantic segmentation models to process color images and publish those topics.

+
+

Python dependencies

+
pip3 install torchvision scikit-learn
+
+
+

Detectron

+
python3 -m pip install 'git+https://github.com/facebookresearch/detectron2.git'
+
+
+
+
+
+

Build

+

After installing all the dependencies, you can build the packages. +Clone the project repository into your catkin_ws/src directory. +Then, build the packages with catkin.

+
cd <your_catkin_ws>
+catkin build elevation_mapping_cupy  # The core package
+catkin build convex_plane_decomposition_ros  # If you want to use plane segmentation
+catkin build semantic_sensor  # If you want to use semantic sensors
+
+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/getting_started/introduction.html b/getting_started/introduction.html new file mode 100644 index 00000000..8b5c277a --- /dev/null +++ b/getting_started/introduction.html @@ -0,0 +1,235 @@ + + + + + + + Introduction — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Introduction

+

The Elevaton Mapping CuPy software package represents an advancement in robotic navigation and locomotion. +Integrating with the Robot Operating System (ROS) and utilizing GPU acceleration, this framework enhances point cloud registration and ray casting, +crucial for efficient and accurate robotic movement, particularly in legged robots.

+
+

Used for Various Real-World Applications

+

This software package has been rigorously tested in challenging environments, including the DARPA Subterranean Challenge, +demonstrating its effectiveness in complex, real-world scenarios. +It supports a wide range of applications, from underground exploration to advanced research in legged locomotion and autonomous navigation.

+ +
+
+

Key Features

+
    +

  • Height Drift Compensation: Tackles state estimation drifts that can create mapping artifacts, ensuring more accurate terrain representation.

    • +

  • Visibility Cleanup and Artifact Removal: Raycasting methods and an exclusion zone feature are designed to remove virtual artifacts and correctly interpret overhanging obstacles, preventing misidentification as walls.

    • +

  • Learning-based Traversability Filter: Assesses terrain traversability using local geometry, improving path planning and navigation.

    • +

  • Versatile Locomotion Tools: Incorporates smoothing filters and plane segmentation, optimizing movement across various terrains.

    • +

  • Multi-Modal Elevation Map (MEM) Framework: Allows seamless integration of diverse data like geometry, semantics, and RGB information, enhancing multi-modal robotic perception.

    • +

  • GPU-Enhanced Efficiency: Facilitates rapid processing of large data structures, crucial for real-time applications.

    • +
+
+
+

Overview

+Overview of multi-modal elevation map structure +

Overview of our multi-modal elevation map structure. The framework takes multi-modal images (purple) and multi-modal (blue) point clouds as +input. This data is input into the elevation map by first associating the data to the cells and then fused with different fusion algorithms into the various +layers of the map. Finally the map can be post-processed with various custom plugins to generate new layers (e.g. traversability) or process layer for +external components (e.g. line detection).

+
+
+

Subscribed Topics

+

The subscribed topics are specified under subscribers parameter.

+

Example setup is in elevation_mapping_cupy/config/core/example_setup.yaml.

+
    +

  • /<point_cloud_topic> ([sensor_msgs/PointCloud2])

    +

    The point cloud topic. It can have additional channels for RGB, intensity, etc.

    +
    • +

  • /<image_topic> ([sensor_msgs/Image])

    +

    The image topic. It can have additional channels for RGB, semantic probabilities, image features etc.

    +
    • +

  • /<camera_info> ([sensor_msgs/CameraInfo])

    +

    The camera info topic. It is used to project the point cloud into the image plane.

    +
    • +

  • /<channel_info> ([elevation_map_msgs/ChannelInfo])

    +

    If this topic is configured, the node will subscribe to it and use the information to associate the image channels to the elevation map layers.

    +
    • +

  • /tf ([tf/tfMessage])

    +

    The transformation tree.

    +
    • +

  • The plane segmentation node subscribes to an elevation map topic ([grid_map_msg/GridMap]). This can be configured in +convex_plane_decomposition_ros/config/core/parameters.yaml

    • +
+
+
+

Published Topics

+

For elevation_mapping_cupy, topics are published as set in the rosparam. +You can specify which layers to publish in which fps.

+

Under publishers, you can specify the topic_name, layers basic_layers and fps.

+
publishers:
+    your_topic_name:
+      layers: [ 'list_of_layer_names', 'layer1', 'layer2' ] # Choose from 'elevation', 'variance', 'traversability', 'time' + plugin layers
+      basic_layers: [ 'list of basic layers', 'layer1' ] # basic_layers for valid cell computation (e.g. Rviz): Choose a subset of `layers`.
+      fps: 5.0  # Publish rate. Use smaller value than `map_acquire_fps`.
+
+
+

Example setting in config/parameters.yaml.

+
    +

  • elevation_map_raw ([grid_map_msg/GridMap])

    +

    The entire elevation map.

    +
    • +

  • elevation_map_recordable ([grid_map_msg/GridMap])

    +

    The entire elevation map with slower update rate for visualization and logging.

    +
    • +

  • elevation_map_filter ([grid_map_msg/GridMap])

    +

    The filtered maps using plugins.

    +
    • +
+

The plane segmentation node publishes the following:

+
    +

  • planar_terrain ([convex_plane_decomposition_msgs/PlanarTerrain])

    +

    A custom message that contains the full segmentation as a map together with the boundary information.

    +
    • +

  • filtered_map ([grid_map_msg/GridMap])

    +

    A grid map message to visualize the segmentation and some intermediate results. This information is also part of planar_terrain.

    +
    • +

  • boundaries ([visualization_msgs/MarkerArray])

    +

    A set of polygons that trace the boundaries of the segmented region. Holes and boundaries of a single region are published as separate +markers with the same color.

    +
    • +

  • insets ([visualization_msgs/PolygonArray])

    +

    A set of polygons that are at a slight inward offset from boundaries. There might be more insets than boundaries since the inward +shift can cause a single region to break down into multiple when narrow passages exist.

    +
    • +
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/getting_started/tutorial.html b/getting_started/tutorial.html new file mode 100644 index 00000000..31cb4eaf --- /dev/null +++ b/getting_started/tutorial.html @@ -0,0 +1,208 @@ + + + + + + + Tutorial — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Tutorial

+

This tutorial will guide you through the basic usage of the elevation mapping cupy. +You will learn how to run the plane segmentation node, the sensor node, and the TurtleBot example.

+

If you want to use your own custom plugins, please refer to the Plugins.

+
+

Run

+

Basic usage.

+
roslaunch elevation_mapping_cupy elevation_mapping_cupy.launch
+
+
+

For the plane segmentation node

+
roslaunch convex_plane_decomposition_ros convex_plane_decomposition.launch
+
+
+

For the sensor node

+
roslaunch semantic_sensor semantic_pointcloud.launch
+roslaunch semantic_sensor semantic_image.launch
+
+
+
+
+

Run TurtleBot example

+

First, install turtlebot simulation.

+
sudo apt install ros-noetic-turtlebot3-gazebo ros-noetic-turtlebot3-teleop
+
+
+

Then, you can run the examples. For the basic version:

+
export TURTLEBOT3_MODEL=waffle
+roslaunch elevation_mapping_cupy turtlesim_simple_example.launch
+
+
+

For fusing semantics into the map such as rgb from a multi modal pointcloud:

+Elevation map examples +
export TURTLEBOT3_MODEL=waffle
+roslaunch elevation_mapping_cupy turtlesim_semantic_pointcloud_example.launch
+
+
+

For fusing semantics into the map such as rgb semantics or features from an image:

+
export TURTLEBOT3_MODEL=waffle
+roslaunch elevation_mapping_cupy turtlesim_semantic_image_example.launch
+
+
+

Or, for the version including plane segmentation:

+
catkin build convex_plane_decomposition_ros
+export TURTLEBOT3_MODEL=waffle
+roslaunch elevation_mapping_cupy turtlesim_plane_decomposition_example.launch
+
+
+

To control the robot with a keyboard, a new terminal window needs to be opened. +Then run

+
export TURTLEBOT3_MODEL=waffle
+roslaunch turtlebot3_teleop turtlebot3_teleop_key.launch
+
+
+

Velocity inputs can be sent to the robot by pressing the keys a, w, d, x. To stop the robot completely, press s.

+
+
+

Errors

+

If you build with the install flag under ros melodic, you might get issues with the modules not found:

+
terminate called after throwing an instance of 'pybind11::error_already_set'
+  what():  ModuleNotFoundError: No module named 'elevation_mapping_cupy'
+
+
+

This is because python3 modules are installed into a different location.

+

This can be fixed by including also the python3 modules location in the PYTHONPATH by adding following line into the launch file:

+
<env name="PYTHONPATH" value="<path_to_your_install>/lib/python3/dist-packages:$(env PYTHONPATH)" />
+
+
+

If you get error such as

+
Make Error at /usr/share/cmake-3.16/Modules/FindPackageHandleStandardArgs.cmake:146 (message):
+  Could NOT find PythonInterp: Found unsuitable version "2.7.18", but
+  required is at least "3" (found /usr/bin/python)
+
+
+

Build with option.

+
catkin build elevation_mapping_cupy -DPYTHON_EXECUTABLE=$(which python3)
+
+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/index.html b/index.html new file mode 100644 index 00000000..6a987a19 --- /dev/null +++ b/index.html @@ -0,0 +1,181 @@ + + + + + + + Multi-modal elevation mapping’s documentation — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Multi-modal elevation mapping’s documentation

+

Welcome to elevation mapping documentation

+python tests +documentation +
+

Index

+
+
Introduction - What is elevation mapping cupy
+
Installation - How to install the elevation map
+
Tutorial - How to launch the first elevation map
+
+

This is a ROS package for elevation mapping on GPU. The elevation mapping code is written in python and uses cupy for GPU computation. The +plane segmentation is done independently and runs on CPU. When the plane segmentation is generated, local convex approximations of the +terrain can be efficiently generated.

+Elevation map examples +Overview of the project +
+
+

Citing

+

If you use the elevation mapping cupy, please cite the following paper: +Elevation Mapping for Locomotion and Navigation using GPU

+
+

Hint

+

Elevation Mapping for Locomotion and Navigation using GPU Link

+

Takahiro Miki, Lorenz Wellhausen, Ruben Grandia, Fabian Jenelten, Timon Homberger, Marco Hutter

+
+
@misc{mikielevation2022,
+    doi = {10.48550/ARXIV.2204.12876},
+    author = {Miki, Takahiro and Wellhausen, Lorenz and Grandia, Ruben and Jenelten, Fabian and Homberger, Timon and Hutter, Marco},
+    keywords = {Robotics (cs.RO), FOS: Computer and information sciences, FOS: Computer and information sciences},
+    title = {Elevation Mapping for Locomotion and Navigation using GPU},
+    publisher = {International Conference on Intelligent Robots and Systems (IROS)},
+    year = {2022},
+}
+
+
+

Multi-modal elevation mapping if you use color or semantic layers

+
+

Hint

+

MEM: Multi-Modal Elevation Mapping for Robotics and Learning Link

+

Gian Erni, Jonas Frey, Takahiro Miki, Matias Mattamala, Marco Hutter

+
+
@misc{Erni2023-bs,
+    title = "{MEM}: {Multi-Modal} Elevation Mapping for Robotics and Learning",
+    author = "Erni, Gian and Frey, Jonas and Miki, Takahiro and Mattamala, Matias and Hutter, Marco",
+    publisher = {International Conference on Intelligent Robots and Systems (IROS)},
+    year = {2023},
+}
+
+
+
+
+
+
+
+
+
+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/objects.inv b/objects.inv new file mode 100644 index 00000000..3928ba9c Binary files /dev/null and b/objects.inv differ diff --git a/py-modindex.html b/py-modindex.html new file mode 100644 index 00000000..351f47da --- /dev/null +++ b/py-modindex.html @@ -0,0 +1,216 @@ + + + + + + Python Module Index — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
    • +
  • Python Module Index
    • +
  • +
    • +
+
+
+
+
+ + +

Python Module Index

+ +
+ e | + s +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
 
+ e
+ elevation_mapping_cupy +
    + elevation_mapping_cupy.elevation_mapping +
    + elevation_mapping_cupy.fusion +
    + elevation_mapping_cupy.parameter +
    + elevation_mapping_cupy.plugins.features_pca +
    + elevation_mapping_cupy.plugins.min_filter +
    + elevation_mapping_cupy.plugins.plugin_manager +
    + elevation_mapping_cupy.plugins.robot_centric_elevation +
    + elevation_mapping_cupy.plugins.semantic_filter +
    + elevation_mapping_cupy.plugins.semantic_traversability +
    + elevation_mapping_cupy.plugins.smooth_filter +
    + elevation_mapping_cupy.semantic_map +
 
+ s
+ semantic_sensor +
    + semantic_sensor.image_parameters +
    + semantic_sensor.pointcloud_parameters +
    + semantic_sensor.utils +
+ + +
+
+
+ +
+ +
+

© Copyright 2022, Takahiro Miki, Gian Erni.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/python/elevation_mapping.html b/python/elevation_mapping.html new file mode 100644 index 00000000..b28b6954 --- /dev/null +++ b/python/elevation_mapping.html @@ -0,0 +1,2278 @@ + + + + + + + Elevation mapping cupy — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Elevation mapping cupy

+
+
+class elevation_mapping_cupy.elevation_mapping.ElevationMap(param: Parameter)
+

Bases: object

+

Core elevation mapping class.

+
+
+__init__(param: Parameter)
+
+
Parameters:
+

param (elevation_mapping_cupy.parameter.Parameter)

+
+
+
+ +
+
+clear()
+

Reset all the layers of the elevation & the semantic map.

+
+ +
+
+get_position(position)
+

Return the position of the map center.

+
+
Parameters:
+

position (numpy.ndarray)

+
+
+
+ +
+
+move(delta_position)
+

Shift the map along all three axes according to the input.

+
+
Parameters:
+

delta_position (numpy.ndarray)

+
+
+
+ +
+
+move_to(position, R)
+

Shift the map to an absolute position and update the rotation of the robot.

+
+
Parameters:
+
    +

  • position (numpy.ndarray)

    • +

  • R (cupy._core.core.ndarray)

    • +
+
+
+
+ +
+
+pad_value(x, shift_value, idx=None, value=0.0)
+

Create a padding of the map along x,y-axis according to amount that has shifted.

+
+
Parameters:
+
    +

  • x (cupy._core.core.ndarray)

    • +

  • shift_value (cupy._core.core.ndarray)

    • +

  • idx (Union[None, int, None, None])

    • +

  • value (float)

    • +
+
+
+
+ +
+
+shift_map_xy(delta_pixel)
+

Shift the map along the horizontal axes according to the input.

+
+
Parameters:
+

delta_pixel (cupy._core.core.ndarray)

+
+
+
+ +
+
+shift_map_z(delta_z)
+

Shift the relevant layers along the vertical axis.

+
+
Parameters:
+

delta_z (cupy._core.core.ndarray)

+
+
+
+ +
+
+compile_kernels()
+

Compile all kernels belonging to the elevation map.

+
+ +
+
+compile_image_kernels()
+

Compile kernels related to processing image messages.

+
+ +
+
+shift_translation_to_map_center(t)
+

Deduct the map center to get the translation of a point w.r.t. the map center.

+
+
Parameters:
+

t (cupy._core.core.ndarray) – Absolute point position

+
+
+
+ +
+
+update_map_with_kernel(points_all, channels, R, t, position_noise, orientation_noise)
+

Update map with new measurement.

+
+
Parameters:
+
    +

  • points_all (cupy._core.core.ndarray)

    • +

  • channels (List[str])

    • +

  • R (cupy._core.core.ndarray)

    • +

  • t (cupy._core.core.ndarray)

    • +

  • position_noise (float)

    • +

  • orientation_noise (float)

    • +
+
+
+
+ +
+
+clear_overlap_map(t)
+

Clear overlapping areas around the map center.

+
+
Parameters:
+

t (cupy._core.core.ndarray) – Absolute point position

+
+
+
+ +
+
+get_additive_mean_error()
+

Returns the additive mean error.

+

Returns:

+
+ +
+
+update_variance()
+

Adds the time variacne to the valid cells.

+
+ +
+
+update_time()
+

adds the time interval to the time layer.

+
+ +
+
+update_upper_bound_with_valid_elevation()
+

Filters all invalid cell’s upper_bound and is_upper_bound layers.

+
+ +
+
+input_pointcloud(raw_points: cupy._core.core.ndarray, channels: List[str], R: cupy._core.core.ndarray, t: cupy._core.core.ndarray, position_noise: float, orientation_noise: float)
+

Input the point cloud and fuse the new measurements to update the elevation map.

+
+
Parameters:
+
    +

  • raw_points (cupy._core.core.ndarray)

    • +

  • channels (List[str])

    • +

  • R (cupy._core.core.ndarray)

    • +

  • t (cupy._core.core.ndarray)

    • +

  • position_noise (float)

    • +

  • orientation_noise (float)

    • +
+
+
Return type:
+

None

+
+
+
+ +
+
+input_image(image: List[cupy._core.core.ndarray], channels: List[str], R: cupy._core.core.ndarray, t: cupy._core.core.ndarray, K: cupy._core.core.ndarray, D: cupy._core.core.ndarray, distortion_model: str, image_height: int, image_width: int)
+

Input image and fuse the new measurements to update the elevation map.

+
+
Parameters:
+
    +

  • sub_key (str) – Key used to identify the subscriber configuration

    • +

  • image (List[cupy._core.core.ndarray]) – List of array containing the individual image input channels

    • +

  • R (cupy._core.core.ndarray) – Camera optical center rotation

    • +

  • t (cupy._core.core.ndarray) – Camera optical center translation

    • +

  • K (cupy._core.core.ndarray) – Camera intrinsics

    • +

  • image_height (int) – Image height

    • +

  • image_width (int) – Image width

    • +
+
+
Return type:
+

None

+
+
+
+ +
+
+update_normal(dilated_map)
+

Clear the normal map and then apply the normal kernel with dilated map as input.

+
+
Parameters:
+

dilated_map (cupy._core.core.ndarray)

+
+
+
+ +
+
+process_map_for_publish(input_map, fill_nan=False, add_z=False, xp=cupy)
+

Process the input_map according to the fill_nan and add_z flags.

+
+
Parameters:
+
    +

  • input_map (cupy._core.core.ndarray)

    • +

  • fill_nan (bool)

    • +

  • add_z (bool)

    • +

  • xp (module)

    • +
+
+
Return type:
+

cupy._core.core.ndarray

+
+
+
+ +
+
+get_elevation()
+

Get the elevation layer.

+
+
Returns:
+

elevation layer

+
+
+
+ +
+
+get_variance()
+

Get the variance layer.

+
+
Returns:
+

variance layer

+
+
+
+ +
+
+get_traversability()
+

Get the traversability layer.

+
+
Returns:
+

traversability layer

+
+
+
+ +
+
+get_time()
+

Get the time layer.

+
+
Returns:
+

time layer

+
+
+
+ +
+
+get_upper_bound()
+

Get the upper bound layer.

+
+
Returns:
+

upper bound layer

+
+
Return type:
+

upper_bound

+
+
+
+ +
+
+get_is_upper_bound()
+

Get the is upper bound layer.

+
+
Returns:
+

layer

+
+
Return type:
+

is_upper_bound

+
+
+
+ +
+
+xp_of_array(array)
+

Indicate which library is used for xp.

+
+
Parameters:
+

array (cupy._core.core.ndarray)

+
+
Returns:
+

either np or cp

+
+
Return type:
+

module

+
+
+
+ +
+
+copy_to_cpu(array, data, stream=None)
+

Transforms the data to float32 and if on gpu loads it to cpu.

+
+
Parameters:
+
    +

  • array (cupy._core.core.ndarray)

    • +

  • data (numpy.ndarray)

    • +

  • stream (Union[None, cupy.cuda.stream.Stream, None, None, None, None, None, None, None])

    • +
+
+
+
+ +
+
+exists_layer(name)
+

Check if the layer exists in elevation map or in the semantic map.

+
+
Parameters:
+

name (str) – Layer name

+
+
Returns:
+

Indicates if layer exists.

+
+
Return type:
+

bool

+
+
+
+ +
+
+get_map_with_name_ref(name, data)
+

Load a layer according to the name input to the data input.

+
+
Parameters:
+
    +

  • name (str) – Name of the layer.

    • +

  • data (numpy.ndarray) – Data structure that contains layer.

    • +
+
+
+
+ +
+
+get_normal_maps()
+

Get the normal maps.

+
+
Returns:
+

the three normal values for each cell

+
+
Return type:
+

maps

+
+
+
+ +
+
+get_normal_ref(normal_x_data, normal_y_data, normal_z_data)
+

Get the normal maps as reference.

+
+
Parameters:
+
    +

  • normal_x_data

    • +

  • normal_y_data

    • +

  • normal_z_data

    • +
+
+
+
+ +
+
+get_layer(name)
+

Return the layer with the name input.

+
+
Parameters:
+

name – The layers name.

+
+
Returns:
+

The rqeuested layer.

+
+
Return type:
+

return_map

+
+
+
+ +
+
+get_polygon_traversability(polygon, result)
+

Check if input polygons are traversable.

+
+
Parameters:
+
    +

  • polygon (cupy._core.core.ndarray)

    • +

  • result (numpy.ndarray)

    • +
+
+
Return type:
+

Union[None, int]

+
+
+
+ +
+
+get_untraversable_polygon(untraversable_polygon)
+

Copy the untraversable polygons to input untraversable_polygons.

+
+
Parameters:
+

untraversable_polygon (numpy.ndarray)

+
+
+
+ +
+
+initialize_map(points, method='cubic')
+

Initializes the map according to some points and using an approximation according to method.

+
+
Parameters:
+
    +

  • points (numpy.ndarray)

    • +

  • method (str) – Interpolation method [‘linear’, ‘cubic’, ‘nearest’]

    • +
+
+
+
+ +
+ +
+
+class elevation_mapping_cupy.semantic_map.SemanticMap(param: Parameter)
+

Bases: object

+
+
+__init__(param: Parameter)
+
+
Parameters:
+

param (elevation_mapping_cupy.parameter.Parameter)

+
+
+
+ +
+
+clear()
+

Clear the semantic map.

+
+ +
+
+initialize_fusion()
+

Initialize the fusion algorithms.

+
+ +
+
+update_fusion_setting()
+

Update the fusion settings.

+
+ +
+
+add_layer(name)
+

Add a new layer to the semantic map.

+
+
Parameters:
+

name (str) – The name of the new layer.

+
+
+
+ +
+
+pad_value(x, shift_value, idx=None, value=0.0)
+

Create a padding of the map along x,y-axis according to amount that has shifted.

+
+
Parameters:
+
    +

  • x (cupy._core.core.ndarray)

    • +

  • shift_value (cupy._core.core.ndarray)

    • +

  • idx (Union[None, int, None, None])

    • +

  • value (float)

    • +
+
+
+
+ +
+
+shift_map_xy(shift_value)
+

Shift the map along x,y-axis according to shift values.

+
+
Parameters:
+

shift_value

+
+
+
+ +
+
+get_fusion(channels: List[str], channel_fusions: Dict[str, str], layer_specs: Dict[str, str]) → List[str]
+

Get all fusion algorithms that need to be applied to a specific pointcloud.

+
+
Parameters:
+

channels (List[str])

+
+
+
+ +
+
+get_matching_fusion(channel: str, fusion_algs: Dict[str, str])
+

Use regular expression to check if the fusion algorithm matches the channel name.

+
+ +
+
+get_layer_indices(fusion_alg, layer_specs)
+

Get the indices of the layers that are used for a specific fusion algorithm.

+
+
Parameters:
+

fusion_alg (str) – fusion algorithm name

+
+
Returns:
+

indices of the layers

+
+
Return type:
+

cp.array

+
+
+
+ +
+
+get_indices_fusion(pcl_channels: List[str], fusion_alg: str, layer_specs: Dict[str, str])
+

Computes the indices of the channels of the pointcloud and the layers of the semantic map of type fusion_alg.

+
+
Parameters:
+
    +

  • pcl_channels (List[str]) – list of all channel names

    • +

  • fusion_alg (str) – fusion algorithm type we want to use for channel selection

    • +
+
+
Return type:
+

Union[Tuple[List[int], List[int]], Tuple[cupy._core.core.ndarray, cupy._core.core.ndarray]]

+
+
+
+ +
+
+update_layers_pointcloud(points_all, channels, R, t, elevation_map)
+

Update the semantic map with the pointcloud.

+
+
Parameters:
+
    +

  • points_all – semantic point cloud

    • +

  • channels – list of channel names

    • +

  • R – rotation matrix

    • +

  • t – translation vector

    • +

  • elevation_map – elevation map object

    • +
+
+
+
+ +
+
+update_layers_image(image: cupy._core.core.ndarray, channels: List[str], uv_correspondence: cupy._core.core.ndarray, valid_correspondence: cupy._core.core.ndarray, image_height: cupy._core.core.ndarray, image_width: cupy._core.core.ndarray)
+

Update the semantic map with the new image.

+
+
Parameters:
+
    +

  • sub_key

    • +

  • image

    • +

  • uv_correspondence

    • +

  • valid_correspondence

    • +

  • image_height

    • +

  • image_width

    • +
+
+
+
+ +
+
+decode_max(mer)
+

Decode the float32 value into two 16 bit value containing the class probability and the class id.

+
+
Parameters:
+

mer

+
+
Returns:
+

probability +cp.array: class id

+
+
Return type:
+

cp.array

+
+
+
+ +
+
+get_map_with_name(name)
+

Return the map with the given name.

+
+
Parameters:
+

name – layer name

+
+
Returns:
+

map

+
+
Return type:
+

cp.array

+
+
+
+ +
+
+get_rgb(name)
+

Return the rgb map with the given name.

+
+
Parameters:
+

name

+
+
Returns:
+

rgb map

+
+
Return type:
+

cp.array

+
+
+
+ +
+
+get_semantic(name)
+

Return the semantic map layer with the given name.

+
+
Parameters:
+

name (str) – layer name

+
+
Returns:
+

semantic map layer

+
+
Return type:
+

cp.array

+
+
+
+ +
+
+process_map_for_publish(input_map)
+

Remove padding.

+
+
Parameters:
+

input_map (cp.array) – map layer

+
+
Returns:
+

map layer without padding

+
+
Return type:
+

cp.array

+
+
+
+ +
+
+get_index(name)
+

Return the index of the layer with the given name.

+
+
Parameters:
+

name (str)

+
+
Returns:
+

index

+
+
Return type:
+

int

+
+
+
+ +
+ +
+
+class elevation_mapping_cupy.parameter.Parameter(*args: Any, **kwargs: Any)
+

Bases: Serializable

+

This class holds the parameters for the elevation mapping algorithm.

+
+
+resolution
+

The resolution in meters. +(Default: 0.04)

+
+
Type:
+

float

+
+
+
+ +
+
+subscriber_cfg
+

The configuration for the subscriber. +(Default: { "front_cam": { "channels": ["rgb", "person"], "topic_name": "/elevation_mapping/pointcloud_semantic", "data_type": "pointcloud", } })

+
+
Type:
+

dict

+
+
+
+ +
+
+additional_layers
+

The additional layers for the map. +(Default: ["color"])

+
+
Type:
+

list

+
+
+
+ +
+
+fusion_algorithms
+

The list of fusion algorithms. +(Default: [ "image_color", "image_exponential", "pointcloud_average", "pointcloud_bayesian_inference", "pointcloud_class_average", "pointcloud_class_bayesian", "pointcloud_class_max", "pointcloud_color", ])

+
+
Type:
+

list

+
+
+
+ +
+
+pointcloud_channel_fusions
+

The fusion for pointcloud channels. +(Default: {"rgb": "color", "default": "class_average"})

+
+
Type:
+

dict

+
+
+
+ +
+
+image_channel_fusions
+

The fusion for image channels. +(Default: {"rgb": "color", "default": "exponential"})

+
+
Type:
+

dict

+
+
+
+ +
+
+data_type
+

The data type for the map. +(Default: np.float32)

+
+
Type:
+

str

+
+
+
+ +
+
+average_weight
+

The weight for the average fusion. +(Default: 0.5)

+
+
Type:
+

float

+
+
+
+ +
+
+map_length
+

The map’s size in meters. +(Default: 8.0)

+
+
Type:
+

float

+
+
+
+ +
+
+sensor_noise_factor
+

The point’s noise is sensor_noise_factor*z^2 (z is distance from sensor). +(Default: 0.05)

+
+
Type:
+

float

+
+
+
+ +
+
+mahalanobis_thresh
+

Points outside this distance is outlier. +(Default: 2.0)

+
+
Type:
+

float

+
+
+
+ +
+
+outlier_variance
+

If point is outlier, add this value to the cell. +(Default: 0.01)

+
+
Type:
+

float

+
+
+
+ +
+
+drift_compensation_variance_inlier
+

Cells under this value is used for drift compensation. +(Default: 0.1)

+
+
Type:
+

float

+
+
+
+ +
+
+time_variance
+

Add this value when update_variance is called. +(Default: 0.01)

+
+
Type:
+

float

+
+
+
+ +
+
+time_interval
+

Time layer is updated with this interval. +(Default: 0.1)

+
+
Type:
+

float

+
+
+
+ +
+
+max_variance
+

The maximum variance for each cell. +(Default: 1.0)

+
+
Type:
+

float

+
+
+
+ +
+
+dilation_size
+

The dilation filter size before traversability filter. +(Default: 2)

+
+
Type:
+

float

+
+
+
+ +
+
+dilation_size_initialize
+

The dilation size after the init. +(Default: 10)

+
+
Type:
+

float

+
+
+
+ +
+
+drift_compensation_alpha
+

The drift compensation alpha for smoother update of drift compensation. +(Default: 1.0)

+
+
Type:
+

float

+
+
+
+ +
+
+traversability_inlier
+

Cells with higher traversability are used for drift compensation. +(Default: 0.1)

+
+
Type:
+

float

+
+
+
+ +
+
+wall_num_thresh
+

If there are more points than this value, only higher points than the current height are used to make the wall more sharp. +(Default: 100)

+
+
Type:
+

float

+
+
+
+ +
+
+min_height_drift_cnt
+

Drift compensation only happens if the valid cells are more than this number. +(Default: 100)

+
+
Type:
+

float

+
+
+
+ +
+
+max_ray_length
+

The maximum length for ray tracing. +(Default: 2.0)

+
+
Type:
+

float

+
+
+
+ +
+
+cleanup_step
+

Substitute this value from validity layer at visibility cleanup. +(Default: 0.01)

+
+
Type:
+

float

+
+
+
+ +
+
+cleanup_cos_thresh
+

Substitute this value from validity layer at visibility cleanup. +(Default: 0.5)

+
+
Type:
+

float

+
+
+
+ +
+
+min_valid_distance
+

Points with shorter distance will be filtered out. +(Default: 0.3)

+
+
Type:
+

float

+
+
+
+ +
+
+max_height_range
+

Points higher than this value from sensor will be filtered out to disable ceiling. +(Default: 1.0)

+
+
Type:
+

float

+
+
+
+ +
+
+ramped_height_range_a
+

If z > max(d - ramped_height_range_b, 0) * ramped_height_range_a + ramped_height_range_c, reject. +(Default: 0.3)

+
+
Type:
+

float

+
+
+
+ +
+
+ramped_height_range_b
+

If z > max(d - ramped_height_range_b, 0) * ramped_height_range_a + ramped_height_range_c, reject. +(Default: 1.0)

+
+
Type:
+

float

+
+
+
+ +
+
+ramped_height_range_c
+

If z > max(d - ramped_height_range_b, 0) * ramped_height_range_a + ramped_height_range_c, reject. +(Default: 0.2)

+
+
Type:
+

float

+
+
+
+ +
+
+safe_thresh
+

If traversability is smaller, it is counted as unsafe cell. +(Default: 0.5)

+
+
Type:
+

float

+
+
+
+ +
+
+safe_min_thresh
+

Polygon is unsafe if there exists lower traversability than this. +(Default: 0.5)

+
+
Type:
+

float

+
+
+
+ +
+
+max_unsafe_n
+

If the number of cells under safe_thresh exceeds this value, polygon is unsafe. +(Default: 20)

+
+
Type:
+

int

+
+
+
+ +
+
+checker_layer
+

Layer used for checking safety. +(Default: "traversability")

+
+
Type:
+

str

+
+
+
+ +
+
+min_filter_size
+

The minimum size for the filter. +(Default: 5)

+
+
Type:
+

int

+
+
+
+ +
+
+min_filter_iteration
+

The minimum number of iterations for the filter. +(Default: 3)

+
+
Type:
+

int

+
+
+
+ +
+
+max_drift
+

The maximum drift for the compensation. +(Default: 0.10)

+
+
Type:
+

float

+
+
+
+ +
+
+overlap_clear_range_xy
+

XY range [m] for clearing overlapped area. This defines the valid area for overlap clearance. (used for multi floor setting) +(Default: 4.0)

+
+
Type:
+

float

+
+
+
+ +
+
+overlap_clear_range_z
+

Z range [m] for clearing overlapped area. Cells outside this range will be cleared. (used for multi floor setting) +(Default: 2.0)

+
+
Type:
+

float

+
+
+
+ +
+
+enable_edge_sharpen
+

Enable edge sharpening. +(Default: True)

+
+
Type:
+

bool

+
+
+
+ +
+
+enable_drift_compensation
+

Enable drift compensation. +(Default: True)

+
+
Type:
+

bool

+
+
+
+ +
+
+enable_visibility_cleanup
+

Enable visibility cleanup. +(Default: True)

+
+
Type:
+

bool

+
+
+
+ +
+
+enable_overlap_clearance
+

Enable overlap clearance. +(Default: True)

+
+
Type:
+

bool

+
+
+
+ +
+
+use_only_above_for_upper_bound
+

Use only above for upper bound. +(Default: True)

+
+
Type:
+

bool

+
+
+
+ +
+
+use_chainer
+

Use chainer as a backend of traversability filter or pytorch. If false, it uses pytorch. Pytorch requires ~2GB more GPU memory compared to chainer but runs faster. +(Default: True)

+
+
Type:
+

bool

+
+
+
+ +
+
+position_noise_thresh
+

If the position change is bigger than this value, the drift compensation happens. +(Default: 0.1)

+
+
Type:
+

float

+
+
+
+ +
+
+orientation_noise_thresh
+

If the orientation change is bigger than this value, the drift compensation happens. +(Default: 0.1)

+
+
Type:
+

float

+
+
+
+ +
+
+plugin_config_file
+

Configuration file for the plugin. +(Default: "config/plugin_config.yaml")

+
+
Type:
+

str

+
+
+
+ +
+
+weight_file
+

Weight file for traversability filter. +(Default: "config/weights.dat")

+
+
Type:
+

str

+
+
+
+ +
+
+initial_variance
+

Initial variance for each cell. +(Default: 10.0)

+
+
Type:
+

float

+
+
+
+ +
+
+initialized_variance
+

Initialized variance for each cell. +(Default: 10.0)

+
+
Type:
+

float

+
+
+
+ +
+
+w1
+

Weights for the first layer. +(Default: np.zeros((4, 1, 3, 3)))

+
+
Type:
+

numpy.ndarray

+
+
+
+ +
+
+w2
+

Weights for the second layer. +(Default: np.zeros((4, 1, 3, 3)))

+
+
Type:
+

numpy.ndarray

+
+
+
+ +
+
+w3
+

Weights for the third layer. +(Default: np.zeros((4, 1, 3, 3)))

+
+
Type:
+

numpy.ndarray

+
+
+
+ +
+
+w_out
+

Weights for the output layer. +(Default: np.zeros((1, 12, 1, 1)))

+
+
Type:
+

numpy.ndarray

+
+
+
+ +
+
+true_map_length
+

True length of the map. +(Default: None)

+
+
Type:
+

float

+
+
+
+ +
+
+cell_n
+

Number of cells in the map. +(Default: None)

+
+
Type:
+

int

+
+
+
+ +
+
+true_cell_n
+

True number of cells in the map. +(Default: None)

+
+
Type:
+

int

+
+
+
+ +
+
+resolution: float = 0.04
+
+ +
+
+subscriber_cfg: dict
+
+ +
+
+additional_layers: list
+
+ +
+
+fusion_algorithms: list
+
+ +
+
+pointcloud_channel_fusions: dict
+
+ +
+
+image_channel_fusions: dict
+
+ +
+
+average_weight: float = 0.5
+
+ +
+
+map_length: float = 8.0
+
+ +
+
+sensor_noise_factor: float = 0.05
+
+ +
+
+mahalanobis_thresh: float = 2.0
+
+ +
+
+outlier_variance: float = 0.01
+
+ +
+
+drift_compensation_variance_inlier: float = 0.1
+
+ +
+
+time_variance: float = 0.01
+
+ +
+
+time_interval: float = 0.1
+
+ +
+
+max_variance: float = 1.0
+
+ +
+
+dilation_size: float = 2
+
+ +
+
+dilation_size_initialize: float = 10
+
+ +
+
+drift_compensation_alpha: float = 1.0
+
+ +
+
+traversability_inlier: float = 0.1
+
+ +
+
+wall_num_thresh: float = 100
+
+ +
+
+min_height_drift_cnt: float = 100
+
+ +
+
+max_ray_length: float = 2.0
+
+ +
+
+cleanup_step: float = 0.01
+
+ +
+
+cleanup_cos_thresh: float = 0.5
+
+ +
+
+min_valid_distance: float = 0.3
+
+ +
+
+max_height_range: float = 1.0
+
+ +
+
+ramped_height_range_a: float = 0.3
+
+ +
+
+ramped_height_range_b: float = 1.0
+
+ +
+
+ramped_height_range_c: float = 0.2
+
+ +
+
+safe_thresh: float = 0.5
+
+ +
+
+safe_min_thresh: float = 0.5
+
+ +
+
+max_unsafe_n: int = 20
+
+ +
+
+checker_layer: str = 'traversability'
+
+ +
+
+min_filter_size: int = 5
+
+ +
+
+min_filter_iteration: int = 3
+
+ +
+
+max_drift: float = 0.1
+
+ +
+
+overlap_clear_range_xy: float = 4.0
+
+ +
+
+overlap_clear_range_z: float = 2.0
+
+ +
+
+enable_edge_sharpen: bool = True
+
+ +
+
+enable_drift_compensation: bool = True
+
+ +
+
+enable_visibility_cleanup: bool = True
+
+ +
+
+enable_overlap_clearance: bool = True
+
+ +
+
+use_only_above_for_upper_bound: bool = True
+
+ +
+
+use_chainer: bool = True
+
+ +
+
+position_noise_thresh: float = 0.1
+
+ +
+
+orientation_noise_thresh: float = 0.1
+
+ +
+
+plugin_config_file: str = 'config/plugin_config.yaml'
+
+ +
+
+weight_file: str = 'config/weights.dat'
+
+ +
+
+initial_variance: float = 10.0
+
+ +
+
+initialized_variance: float = 10.0
+
+ +
+
+w1: numpy.ndarray
+
+ +
+
+w2: numpy.ndarray
+
+ +
+
+w3: numpy.ndarray
+
+ +
+
+w_out: numpy.ndarray
+
+ +
+
+true_map_length: float = None
+
+ +
+
+cell_n: int = None
+
+ +
+
+true_cell_n: int = None
+
+ +
+
+load_weights(filename)
+

Load weights from a file into the model’s parameters.

+
+
Parameters:
+

filename (str) – The path to the file containing the weights.

+
+
+
+ +
+
+get_names()
+

Get the names of the parameters.

+
+
Returns:
+

A list of parameter names.

+
+
Return type:
+

list

+
+
+
+ +
+
+get_types()
+

Get the types of the parameters.

+
+
Returns:
+

A list of parameter types.

+
+
Return type:
+

list

+
+
+
+ +
+
+set_value(name, value)
+

Set the value of a parameter.

+
+
Parameters:
+
    +

  • name (str) – The name of the parameter.

    • +

  • value (any) – The new value for the parameter.

    • +
+
+
+
+ +
+
+get_value(name)
+

Get the value of a parameter.

+
+
Parameters:
+

name (str) – The name of the parameter.

+
+
Returns:
+

The value of the parameter.

+
+
Return type:
+

any

+
+
+
+ +
+
+update()
+

Update the parameters related to the map size and resolution.

+
+ +
+
+__init__(resolution: float = 0.04, subscriber_cfg: dict = <factory>, additional_layers: list = <factory>, fusion_algorithms: list = <factory>, pointcloud_channel_fusions: dict = <factory>, image_channel_fusions: dict = <factory>, data_type: str = numpy.float32, average_weight: float = 0.5, map_length: float = 8.0, sensor_noise_factor: float = 0.05, mahalanobis_thresh: float = 2.0, outlier_variance: float = 0.01, drift_compensation_variance_inlier: float = 0.1, time_variance: float = 0.01, time_interval: float = 0.1, max_variance: float = 1.0, dilation_size: float = 2, dilation_size_initialize: float = 10, drift_compensation_alpha: float = 1.0, traversability_inlier: float = 0.1, wall_num_thresh: float = 100, min_height_drift_cnt: float = 100, max_ray_length: float = 2.0, cleanup_step: float = 0.01, cleanup_cos_thresh: float = 0.5, min_valid_distance: float = 0.3, max_height_range: float = 1.0, ramped_height_range_a: float = 0.3, ramped_height_range_b: float = 1.0, ramped_height_range_c: float = 0.2, safe_thresh: float = 0.5, safe_min_thresh: float = 0.5, max_unsafe_n: int = 20, checker_layer: str = 'traversability', min_filter_size: int = 5, min_filter_iteration: int = 3, max_drift: float = 0.1, overlap_clear_range_xy: float = 4.0, overlap_clear_range_z: float = 2.0, enable_edge_sharpen: bool = True, enable_drift_compensation: bool = True, enable_visibility_cleanup: bool = True, enable_overlap_clearance: bool = True, use_only_above_for_upper_bound: bool = True, use_chainer: bool = True, position_noise_thresh: float = 0.1, orientation_noise_thresh: float = 0.1, plugin_config_file: str = 'config/plugin_config.yaml', weight_file: str = 'config/weights.dat', initial_variance: float = 10.0, initialized_variance: float = 10.0, w1: numpy.ndarray = <factory>, w2: numpy.ndarray = <factory>, w3: numpy.ndarray = <factory>, w_out: numpy.ndarray = <factory>, true_map_length: float = None, cell_n: int = None, true_cell_n: int = None) → None
+
+ +
+ +
+
+class elevation_mapping_cupy.plugins.plugin_manager.PluginParams(name: str, layer_name: str, fill_nan: bool = False, is_height_layer: bool = False)
+

Bases: object

+
+
+name: str
+
+ +
+
+layer_name: str
+
+ +
+
+fill_nan: bool = False
+
+ +
+
+is_height_layer: bool = False
+
+ +
+
+__init__(name: str, layer_name: str, fill_nan: bool = False, is_height_layer: bool = False) → None
+
+ +
+ +
+
+class elevation_mapping_cupy.plugins.plugin_manager.PluginBase(*args, **kwargs)
+

Bases: ABC

+

This is a base class of Plugins

+
+
+__init__(*args, **kwargs)
+
+
Parameters:
+
    +

  • plugin_params – PluginParams

    • +

  • callback (The parameter of)

    • +
+
+
+
+ +
+
+get_layer_data(elevation_map: cupy.ndarray, layer_names: List[str], plugin_layers: cupy.ndarray, plugin_layer_names: List[str], semantic_map: cupy.ndarray, semantic_layer_names: List[str], name: str) → cupy.ndarray | None
+

Retrieve a copy of the layer data from the elevation, plugin, or semantic maps based on the layer name.

+
+
Parameters:
+
    +

  • elevation_map (cp.ndarray) – The elevation map containing various layers.

    • +

  • layer_names (List[str]) – A list of names for each layer in the elevation map.

    • +

  • plugin_layers (cp.ndarray) – The plugin layers containing additional data.

    • +

  • plugin_layer_names (List[str]) – A list of names for each layer in the plugin layers.

    • +

  • semantic_map (cp.ndarray) – The semantic map containing various layers.

    • +

  • semantic_layer_names (List[str]) – A list of names for each layer in the semantic map.

    • +

  • name (str) – The name of the layer to retrieve.

    • +
+
+
Returns:
+

A copy of the requested layer as a cupy ndarray if found, otherwise None.

+
+
Return type:
+

Optional[cp.ndarray]

+
+
+
+ +
+ +
+
+class elevation_mapping_cupy.plugins.plugin_manager.PluginManager(cell_n: int)
+

Bases: object

+

This manages the plugins.

+
+
+__init__(cell_n: int)
+
+ +
+
+init(plugin_params: List[PluginParams], extra_params: List[Dict])
+
+ +
+
+load_plugin_settings(file_path: str)
+
+ +
+
+get_layer_names()
+
+ +
+
+get_plugin_names()
+
+ +
+
+get_plugin_index_with_name(name: str) → int
+
+ +
+
+get_layer_index_with_name(name: str) → int
+
+ +
+
+update_with_name(name: str, elevation_map: cupy.ndarray, layer_names: List[str], semantic_map=None, semantic_params=None, rotation=None, elements_to_shift={})
+
+ +
+
+get_map_with_name(name: str) → cupy.ndarray
+
+ +
+
+get_param_with_name(name: str) → PluginParams
+
+ +
+ +
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/python/index.html b/python/index.html new file mode 100644 index 00000000..b3f9b681 --- /dev/null +++ b/python/index.html @@ -0,0 +1,430 @@ + + + + + + + Python software — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Python software

+
+ +
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/python/semantic_sensor.html b/python/semantic_sensor.html new file mode 100644 index 00000000..893386ab --- /dev/null +++ b/python/semantic_sensor.html @@ -0,0 +1,564 @@ + + + + + + + Semantic Pointcloud — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Semantic Pointcloud

+
+
+class semantic_sensor.pointcloud_parameters.FeatureExtractorParameter(name: str = 'DINO', interpolation: str = 'bilinear', model: str = 'vit_small', patch_size: int = 16, dim: int = 5, dropout: bool = False, dino_feat_type: str = 'feat', projection_type: str = 'nonlinear', input_size: list = <factory>, feature_image_topic: str = '/semantic_sensor/feature_image', pcl: bool = True)
+

Bases: Serializable

+
+
+name: str = 'DINO'
+
+ +
+
+interpolation: str = 'bilinear'
+
+ +
+
+model: str = 'vit_small'
+
+ +
+
+patch_size: int = 16
+
+ +
+
+dim: int = 5
+
+ +
+
+dropout: bool = False
+
+ +
+
+dino_feat_type: str = 'feat'
+
+ +
+
+projection_type: str = 'nonlinear'
+
+ +
+
+input_size: list = Field(name=None,type=None,default=<dataclasses._MISSING_TYPE object>,default_factory=<function PointcloudParameter.<lambda>>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=<dataclasses._MISSING_TYPE object>,_field_type=None)
+
+ +
+
+feature_image_topic: str = '/semantic_sensor/feature_image'
+
+ +
+
+pcl: bool = True
+
+ +
+
+__init__(name: str = 'DINO', interpolation: str = 'bilinear', model: str = 'vit_small', patch_size: int = 16, dim: int = 5, dropout: bool = False, dino_feat_type: str = 'feat', projection_type: str = 'nonlinear', input_size: list = <factory>, feature_image_topic: str = '/semantic_sensor/feature_image', pcl: bool = True) → None
+
+ +
+
+decode_into_subclasses: ClassVar[bool] = False
+
+ +
+ +
+
+class semantic_sensor.pointcloud_parameters.PointcloudParameter(sensor_name: str = 'camera', topic_name: str = '/elvation_mapping/pointcloud_semantic', channels: list = <factory>, fusion: list = <factory>, semantic_segmentation: bool = False, segmentation_model: str = 'lraspp_mobilenet_v3_large', publish_segmentation_image: bool = False, segmentation_image_topic: str = '/semantic_sensor/sem_seg', pub_all: bool = False, show_label_legend: bool = False, cam_info_topic: str = '/zed2i/zed_node/depth/camera_info', image_topic: str = '/zed2i/zed_node/left/image_rect_color', depth_topic: str = '/zed2i/zed_node/depth/depth_registered', cam_frame: str = 'zed2i_right_camera_optical_frame', confidence: bool = False, confidence_topic: str = '/zed2i/zed_node/confidence/confidence_map', confidence_threshold: int = 10, feature_extractor: bool = False, publish_feature_image: bool = False, feature_config: semantic_sensor.pointcloud_parameters.FeatureExtractorParameter = <class 'semantic_sensor.pointcloud_parameters.FeatureExtractorParameter'>)
+

Bases: Serializable

+
+
+sensor_name: str = 'camera'
+
+ +
+
+topic_name: str = '/elvation_mapping/pointcloud_semantic'
+
+ +
+
+channels: list
+
+ +
+
+fusion: list
+
+ +
+
+semantic_segmentation: bool = False
+
+ +
+
+segmentation_model: str = 'lraspp_mobilenet_v3_large'
+
+ +
+
+publish_segmentation_image: bool = False
+
+ +
+
+segmentation_image_topic: str = '/semantic_sensor/sem_seg'
+
+ +
+
+pub_all: bool = False
+
+ +
+
+show_label_legend: bool = False
+
+ +
+
+cam_info_topic: str = '/zed2i/zed_node/depth/camera_info'
+
+ +
+
+image_topic: str = '/zed2i/zed_node/left/image_rect_color'
+
+ +
+
+depth_topic: str = '/zed2i/zed_node/depth/depth_registered'
+
+ +
+
+cam_frame: str = 'zed2i_right_camera_optical_frame'
+
+ +
+
+confidence: bool = False
+
+ +
+
+confidence_topic: str = '/zed2i/zed_node/confidence/confidence_map'
+
+ +
+
+confidence_threshold: int = 10
+
+ +
+
+feature_extractor: bool = False
+
+ +
+
+publish_feature_image: bool = False
+
+ +
+
+feature_config
+

alias of FeatureExtractorParameter

+
+ +
+
+__init__(sensor_name: str = 'camera', topic_name: str = '/elvation_mapping/pointcloud_semantic', channels: list = <factory>, fusion: list = <factory>, semantic_segmentation: bool = False, segmentation_model: str = 'lraspp_mobilenet_v3_large', publish_segmentation_image: bool = False, segmentation_image_topic: str = '/semantic_sensor/sem_seg', pub_all: bool = False, show_label_legend: bool = False, cam_info_topic: str = '/zed2i/zed_node/depth/camera_info', image_topic: str = '/zed2i/zed_node/left/image_rect_color', depth_topic: str = '/zed2i/zed_node/depth/depth_registered', cam_frame: str = 'zed2i_right_camera_optical_frame', confidence: bool = False, confidence_topic: str = '/zed2i/zed_node/confidence/confidence_map', confidence_threshold: int = 10, feature_extractor: bool = False, publish_feature_image: bool = False, feature_config: ~semantic_sensor.pointcloud_parameters.FeatureExtractorParameter = <class 'semantic_sensor.pointcloud_parameters.FeatureExtractorParameter'>) → None
+
+ +
+
+decode_into_subclasses: ClassVar[bool] = False
+
+ +
+ +
+
+class semantic_sensor.image_parameters.FeatureExtractorParameter(name: str = 'DINO', interpolation: str = 'bilinear', model: str = 'vit_small', patch_size: int = 16, dim: int = 10, dropout: bool = False, dino_feat_type: str = 'feat', projection_type: str = 'nonlinear', input_size: list = <factory>, pcl: bool = False)
+

Bases: Serializable

+
+
+name: str = 'DINO'
+
+ +
+
+interpolation: str = 'bilinear'
+
+ +
+
+model: str = 'vit_small'
+
+ +
+
+patch_size: int = 16
+
+ +
+
+dim: int = 10
+
+ +
+
+dropout: bool = False
+
+ +
+
+dino_feat_type: str = 'feat'
+
+ +
+
+projection_type: str = 'nonlinear'
+
+ +
+
+input_size: list
+
+ +
+
+pcl: bool = False
+
+ +
+
+__init__(name: str = 'DINO', interpolation: str = 'bilinear', model: str = 'vit_small', patch_size: int = 16, dim: int = 10, dropout: bool = False, dino_feat_type: str = 'feat', projection_type: str = 'nonlinear', input_size: list = <factory>, pcl: bool = False) → None
+
+ +
+
+decode_into_subclasses: ClassVar[bool] = False
+
+ +
+ +
+
+class semantic_sensor.image_parameters.ImageParameter(image_topic: str = '/alphasense_driver_ros/cam4/debayered', semantic_segmentation: bool = True, segmentation_model: str = 'detectron_coco_panoptic_fpn_R_101_3x', show_label_legend: bool = False, channels: list = <factory>, publish_topic: str = 'semantic_seg', publish_image_topic: str = 'semantic_seg_img', channel_info_topic: str = 'channel_info', feature_extractor: bool = False, feature_config: semantic_sensor.image_parameters.FeatureExtractorParameter = <class 'semantic_sensor.image_parameters.FeatureExtractorParameter'>, feature_topic: str = 'semantic_seg_feat', feat_image_topic: str = 'semantic_seg_feat_im', feat_channel_info_topic: str = 'feat_channel_info', resize: float = None, camera_info_topic: str = 'camera_info')
+

Bases: Serializable

+
+
+image_topic: str = '/alphasense_driver_ros/cam4/debayered'
+
+ +
+
+semantic_segmentation: bool = True
+
+ +
+
+segmentation_model: str = 'detectron_coco_panoptic_fpn_R_101_3x'
+
+ +
+
+show_label_legend: bool = False
+
+ +
+
+channels: list
+
+ +
+
+publish_topic: str = 'semantic_seg'
+
+ +
+
+publish_image_topic: str = 'semantic_seg_img'
+
+ +
+
+channel_info_topic: str = 'channel_info'
+
+ +
+
+feature_extractor: bool = False
+
+ +
+
+feature_config
+

alias of FeatureExtractorParameter

+
+ +
+
+feature_topic: str = 'semantic_seg_feat'
+
+ +
+
+feat_image_topic: str = 'semantic_seg_feat_im'
+
+ +
+
+feat_channel_info_topic: str = 'feat_channel_info'
+
+ +
+
+resize: float = None
+
+ +
+
+camera_info_topic: str = 'camera_info'
+
+ +
+
+__init__(image_topic: str = '/alphasense_driver_ros/cam4/debayered', semantic_segmentation: bool = True, segmentation_model: str = 'detectron_coco_panoptic_fpn_R_101_3x', show_label_legend: bool = False, channels: list = <factory>, publish_topic: str = 'semantic_seg', publish_image_topic: str = 'semantic_seg_img', channel_info_topic: str = 'channel_info', feature_extractor: bool = False, feature_config: ~semantic_sensor.image_parameters.FeatureExtractorParameter = <class 'semantic_sensor.image_parameters.FeatureExtractorParameter'>, feature_topic: str = 'semantic_seg_feat', feat_image_topic: str = 'semantic_seg_feat_im', feat_channel_info_topic: str = 'feat_channel_info', resize: float = None, camera_info_topic: str = 'camera_info') → None
+
+ +
+
+decode_into_subclasses: ClassVar[bool] = False
+
+ +
+ +
+
+semantic_sensor.utils.encode_max(maxim, index)
+
+ +
+
+semantic_sensor.utils.decode_max(mer)
+
+ +
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/search.html b/search.html new file mode 100644 index 00000000..47604103 --- /dev/null +++ b/search.html @@ -0,0 +1,136 @@ + + + + + + Search — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
    • +
  • Search
    • +
  • +
    • +
+
+
+
+
+ + + + +
+ +
+ +
+
+
+ +
+ +
+

© Copyright 2022, Takahiro Miki, Gian Erni.

+
+ + Built with Sphinx using a + theme + provided by Read the Docs. + + +
+
+
+
+
+ + + + + + + + + \ No newline at end of file diff --git a/searchindex.js b/searchindex.js new file mode 100644 index 00000000..b096aa29 --- /dev/null +++ b/searchindex.js @@ -0,0 +1 @@ +Search.setIndex({"alltitles": {"1. Min filter": [[11, "module-elevation_mapping_cupy.plugins.min_filter"]], "2. Inpainting": [[11, "inpainting"]], "3. Smooth Filter": [[11, "module-elevation_mapping_cupy.plugins.smooth_filter"]], "4. Robot centric elevation": [[11, "module-elevation_mapping_cupy.plugins.robot_centric_elevation"]], "5. Semantic Filter": [[11, "module-elevation_mapping_cupy.plugins.semantic_filter"]], "6. Semantic traversability": [[11, "module-elevation_mapping_cupy.plugins.semantic_traversability"]], "7. Features PCA": [[11, "module-elevation_mapping_cupy.plugins.features_pca"]], "Build": [[2, "build"]], "CGAL": [[2, "cgal"]], "CUDA": [[1, "cuda"]], "CUDA & cuDNN": [[2, "cuda-cudnn"]], "CUDA CuDNN": [[2, "id5"]], "Citing": [[0, "citing"], [5, "citing"]], "Core Parameters": [[9, "core-parameters"]], "Create a plugin": [[11, "create-a-plugin"]], "Cuda installation": [[1, "cuda-installation"]], "Cupy": [[2, "id2"]], "Dockers": [[2, "dockers"]], "Eigen": [[2, "eigen"]], "Elevation mapping cupy": [[6, "module-elevation_mapping_cupy.elevation_mapping"]], "Errors": [[4, "errors"]], "Existing plugins": [[11, "existing-plugins"]], "Index": [[0, "index"], [5, "index"]], "Installation": [[2, "installation"]], "Introduction": [[3, "introduction"]], "Key Features": [[3, "key-features"]], "Multi-modal elevation mapping\u2019s documentation": [[0, "multi-modal-elevation-mapping-s-documentation"], [5, "multi-modal-elevation-mapping-s-documentation"]], "On Desktop or Laptop with NVIDIA GPU": [[2, "on-desktop-or-laptop-with-nvidia-gpu"]], "On Jetson": [[2, "on-jetson"]], "OpenCV": [[2, "opencv"]], "Overview": [[3, "overview"]], "Parameters": [[9, "parameters"]], "Plane Segmentation": [[10, "plane-segmentation"]], "Plane segmentation dependencies": [[2, "plane-segmentation-dependencies"]], "Plugin configurations": [[9, "plugin-configurations"]], "Plugins": [[11, "plugins"]], "Published Topics": [[3, "published-topics"]], "Python dependencies": [[2, "python-dependencies"], [2, "id6"], [2, "id9"]], "Python software": [[7, "python-software"]], "ROS dependencies": [[2, "ros-dependencies"]], "ROS package dependencies": [[2, "ros-package-dependencies"]], "Robot Setup Configurations": [[9, "robot-setup-configurations"]], "Run": [[4, "run"]], "Run TurtleBot example": [[4, "run-turtlebot-example"]], "Semantic Pointcloud": [[8, "module-semantic_sensor.pointcloud_parameters"]], "Semantic Sensors": [[2, "semantic-sensors"]], "Semantic pointcloud": [[12, "semantic-pointcloud"]], "Semantics": [[12, "semantics"]], "Sensor parameter": [[9, "sensor-parameter"]], "Subscribed Topics": [[3, "subscribed-topics"]], "Traversability filter": [[2, "traversability-filter"]], "Tutorial": [[4, "tutorial"]], "Used for Various Real-World Applications": [[3, "used-for-various-real-world-applications"]], "cuDNN": [[1, "cudnn"]], "semantic extension of the elevation map": [[12, "semantic-extension-of-the-elevation-map"]]}, "docnames": ["documentation", "getting_started/cuda_installation", "getting_started/installation", "getting_started/introduction", "getting_started/tutorial", "index", "python/elevation_mapping", "python/index", "python/semantic_sensor", "usage/parameters", "usage/plane_segmentation", "usage/plugins", "usage/semantics"], "envversion": {"sphinx": 61, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, 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"Parameters", "Plane Segmentation", "Plugins", "Semantics"], "titleterms": {"": [0, 5], "1": 11, "2": 11, "3": 11, "4": 11, "5": 11, "6": 11, "7": 11, "On": 2, "applic": 3, "build": 2, "centric": 11, "cgal": 2, "cite": [0, 5], "configur": 9, "core": 9, "creat": 11, "cuda": [1, 2], "cudnn": [1, 2], "cupi": [2, 6], "depend": 2, "desktop": 2, "docker": 2, "document": [0, 5], "eigen": 2, "elev": [0, 5, 6, 11, 12], "error": 4, "exampl": 4, "exist": 11, "extens": 12, "featur": [3, 11], "filter": [2, 11], "gpu": 2, "index": [0, 5], "inpaint": 11, "instal": [1, 2], "introduct": 3, "jetson": 2, "kei": 3, "laptop": 2, "map": [0, 5, 6, 12], "min": 11, "modal": [0, 5], "multi": [0, 5], "nvidia": 2, "opencv": 2, "overview": 3, "packag": 2, "paramet": 9, "pca": 11, "plane": [2, 10], "plugin": [9, 11], "pointcloud": [8, 12], "publish": 3, "python": [2, 7], "real": 3, "ro": 2, "robot": [9, 11], "run": 4, "segment": [2, 10], "semant": [2, 8, 11, 12], "sensor": [2, 9], "setup": 9, "smooth": 11, "softwar": 7, "subscrib": 3, "topic": 3, "travers": [2, 11], "turtlebot": 4, "tutori": 4, "us": 3, "variou": 3, "world": 3}}) \ No newline at end of file diff --git a/usage/parameters.html b/usage/parameters.html new file mode 100644 index 00000000..3c0012d5 --- /dev/null +++ b/usage/parameters.html @@ -0,0 +1,360 @@ + + + + + + + Parameters — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Parameters

+

There are three parameter files:

+
    +

  1. Robot Setup Configurations

    2. +

  2. Plugin configurations

    3. +

  3. Core Parameters

    4. +

  4. Sensor parameter

    5. +
+
+

Robot Setup Configurations

+

Such as Publishers and subscribers

+
#### Plugins ########
+plugin_config_file: '$(rospack find elevation_mapping_cupy)/config/core/plugin_config.yaml'
+
+#### Channel Fusions ########
+pointcloud_channel_fusions:
+  rgb: 'color'                # 'color' fusion is used for the 'rgb' channel
+  default: 'average'          # 'average' fusion is used for channels not listed here
+
+image_channel_fusions:
+  rgb: 'color'                # 'color' fusion is used for the 'rgb' channel
+  default: 'exponential'      # 'exponential' fusion is used for channels not listed here
+  feat_.*: 'exponential'      # 'exponential' fusion is also used for any channel starting with 'feat_' Regular expressions can be used for channel names
+
+#### Subscribers ########
+#  pointcloud_sensor_name:
+#    topic_name: '/sensor/pointcloud_semantic'
+#    data_type:  pointcloud  # pointcloud or image
+#
+#  image_sensor_name:
+#    topic_name: '/camera/image_semantic'
+#    data_type:  image  # pointcloud or image
+#    camera_info_topic_name: '/camera/depth/camera_info'
+#    channel_info_topic_name: '/camera/channel_info'
+
+
+subscribers:
+  front_cam:
+    topic_name: '/camera/depth/points'
+    data_type: pointcloud
+  color_cam: # for color camera
+    topic_name: '/camera/rgb/image_raw'
+    camera_info_topic_name: '/camera/depth/camera_info'
+    data_type: image
+  semantic_cam: # for semantic images
+    topic_name: '/front_cam/semantic_image'
+    camera_info_topic_name: '/front_cam/camera/depth/camera_info_resized'
+    channel_info_topic_name: '/front_cam/channel_info'
+    data_type: image
+
+#### Publishers ########
+# topic_name:
+#   layers:               # Choose from 'elevation', 'variance', 'traversability', 'time', 'normal_x', 'normal_y', 'normal_z', 'color', plugin_layer_names
+#   basic_layers:         # basic_layers for valid cell computation (e.g. Rviz): Choose a subset of `layers`.
+#   fps:                  # Publish rate. Use smaller value than `map_acquire_fps`.
+
+publishers:
+  elevation_map_raw:
+    layers: ['elevation', 'traversability', 'variance','rgb']
+    basic_layers: ['elevation']
+    fps: 5.0
+  elevation_map_recordable:
+   layers: ['elevation', 'traversability']
+   basic_layers: ['elevation', 'traversability']
+   fps: 2.0
+  elevation_map_filter:
+    layers: ['min_filter', 'smooth', 'inpaint', 'elevation']
+    basic_layers: ['min_filter']
+    fps: 3.0
+
+
+
+
+

Plugin configurations

+

More informations on the plugins can be found in Plugins.

+
# Settings of the plugins. (The plugins should be stored in script/plugins)
+
+# min_filter fills in minimum value around the invalid cell.
+min_filter:
+  enable: True                                # weather to load this plugin
+  fill_nan: False                             # Fill nans to invalid cells of elevation layer.
+  is_height_layer: True                       # If this is a height layer (such as elevation) or not (such as traversability)
+  layer_name: "min_filter"                    # The layer name.
+  extra_params:                               # This params are passed to the plugin class on initialization.
+    dilation_size: 1                         # The patch size to apply
+    iteration_n: 30                           # The number of iterations
+# Apply smoothing.
+smooth_filter:
+  enable: True
+  fill_nan: False
+  is_height_layer: True
+  layer_name: "smooth"
+  extra_params:
+    input_layer_name: "min_filter"
+# Apply inpainting using opencv
+inpainting:
+  enable: True
+  fill_nan: False
+  is_height_layer: True
+  layer_name: "inpaint"
+  extra_params:
+    method: "telea"                           # telea or ns
+# Apply smoothing for inpainted layer
+erosion:
+  enable: True
+  fill_nan: False
+  is_height_layer: False
+  layer_name: "erosion"
+  extra_params:
+    input_layer_name: "traversability"
+    dilation_size: 3
+    iteration_n: 20
+    reverse: True
+
+
+
+
+

Core Parameters

+
#### Basic parameters ########
+resolution: 0.04                                # resolution in m.
+map_length: 8.0                                 # map's size in m.
+sensor_noise_factor: 0.05                       # point's noise is sensor_noise_factor*z^2 (z is distance from sensor).
+mahalanobis_thresh: 2.0                         # points outside this distance is outlier.
+outlier_variance: 0.01                          # if point is outlier, add this value to the cell.
+drift_compensation_variance_inler: 0.05         # cells under this value is used for drift compensation.
+max_drift: 0.1                                  # drift compensation happens only the drift is smaller than this value (for safety)
+drift_compensation_alpha: 0.1                   # drift compensation alpha for smoother update of drift compensation
+time_variance: 0.0001                           # add this value when update_variance is called.
+max_variance: 100.0                             # maximum variance for each cell.
+initial_variance: 1000.0                         # initial variance for each cell.
+traversability_inlier: 0.9                      # cells with higher traversability are used for drift compensation.
+dilation_size: 3                                # dilation filter size before traversability filter.
+wall_num_thresh: 20                             # if there are more points than this value, only higher points than the current height are used to make the wall more sharp.
+min_height_drift_cnt: 100                       # drift compensation only happens if the valid cells are more than this number.
+position_noise_thresh: 0.01                     # if the position change is bigger than this value, the drift compensation happens.
+orientation_noise_thresh: 0.01                  # if the orientation change is bigger than this value, the drift compensation happens.
+position_lowpass_alpha: 0.2                     # lowpass filter alpha used for detecting movements.
+orientation_lowpass_alpha: 0.2                  # lowpass filter alpha used for detecting movements.
+min_valid_distance: 0.5                         # points with shorter distance will be filtered out.
+max_height_range: 1.0                           # points higher than this value from sensor will be filtered out to disable ceiling.
+ramped_height_range_a: 0.3                      # if z > max(d - ramped_height_range_b, 0) * ramped_height_range_a + ramped_height_range_c, reject.
+ramped_height_range_b: 1.0                      # if z > max(d - ramped_height_range_b, 0) * ramped_height_range_a + ramped_height_range_c, reject.
+ramped_height_range_c: 0.2                      # if z > max(d - ramped_height_range_b, 0) * ramped_height_range_a + ramped_height_range_c, reject.
+update_variance_fps: 5.0                        # fps for updating variance.
+update_pose_fps: 10.0                           # fps for updating pose and shift the center of map.
+time_interval: 0.1                              # Time layer is updated with this interval.
+map_acquire_fps: 5.0                            # Raw map is fetched from GPU memory in this fps.
+publish_statistics_fps: 1.0                     # Publish statistics topic in this fps.
+
+max_ray_length: 10.0                            # maximum length for ray tracing.
+cleanup_step: 0.1                               # subtitute this value from validity layer at visibiltiy cleanup.
+cleanup_cos_thresh: 0.1                         # subtitute this value from validity layer at visibiltiy cleanup.
+
+safe_thresh: 0.7                                # if traversability is smaller, it is counted as unsafe cell.
+safe_min_thresh: 0.4                            # polygon is unsafe if there exists lower traversability than this.
+max_unsafe_n: 10                                # if the number of cells under safe_thresh exceeds this value, polygon is unsafe.
+
+overlap_clear_range_xy: 4.0                     # xy range [m] for clearing overlapped area. this defines the valid area for overlap clearance. (used for multi floor setting)
+overlap_clear_range_z: 2.0                      # z range [m] for clearing overlapped area. cells outside this range will be cleared. (used for multi floor setting)
+
+map_frame: 'odom'                               # The map frame where the odometry source uses.
+base_frame: 'base_footprint'                              # The robot's base frame. This frame will be a center of the map.
+corrected_map_frame: 'odom'
+
+#### Feature toggles ########
+enable_edge_sharpen: true
+enable_visibility_cleanup: true
+enable_drift_compensation: true
+enable_overlap_clearance: true
+enable_pointcloud_publishing: false
+enable_drift_corrected_TF_publishing: false
+enable_normal_color: false                      # If true, the map contains 'color' layer corresponding to normal. Add 'color' layer to the publishers setting if you want to visualize.
+
+#### Traversability filter ########
+use_chainer: false                              # Use chainer as a backend of traversability filter or pytorch. If false, it uses pytorch. pytorch requires ~2GB more GPU memory compared to chainer but runs faster.
+weight_file: '$(rospack find elevation_mapping_cupy)/config/core/weights.dat'               # Weight file for traversability filter
+
+#### Upper bound ########
+use_only_above_for_upper_bound: false
+
+#### Initializer ########
+initialize_method: 'linear'                                         # Choose one from 'nearest', 'linear', 'cubic'
+initialize_frame_id: ['base_footprint']   # One tf (like ['footprint'] ) initializes a square around it.
+initialize_tf_offset: [0.0, 0.0, 0.0, 0.0]                          # z direction. Should be same number as initialize_frame_id.
+dilation_size_initialize: 2                                         # dilation size after the init.
+initialize_tf_grid_size: 0.5                                        # This is not used if number of tf is more than 3.
+use_initializer_at_start: true                                      # Use initializer when the node starts.
+
+#### Default Plugins ########
+plugin_config_file: '$(rospack find elevation_mapping_cupy)/config/core/plugin_config.yaml'
+
+
+
+
+

Sensor parameter

+

More informations on the sensor configurations can be found in Semantics.

+
front_cam_pointcloud:
+  channels: ['rgb', 'chair','sofa',"person" ]
+  fusion: ['color','class_average','class_average','class_average']
+  topic_name: 'front_camera/semantic_pointcloud'
+  semantic_segmentation: True
+  publish_segmentation_image: True
+  segmentation_model: 'lraspp_mobilenet_v3_large' # detectron_coco_panoptic_fpn_R_101_3x, lraspp_mobilenet_v3_large
+  show_label_legend: False
+  data_type: pointcloud
+
+  cam_info_topic: "camera/depth/camera_info"
+  image_topic: "camera/rgb/image_raw"
+  depth_topic: "camera/depth/image_raw"
+  cam_frame: "camera_rgb_optical_frame"
+
+front_cam_image:
+  channels: ['chair','sofa',"person"]
+  fusion_methods: ['exponential','exponential','exponential']
+  publish_topic: 'semantic_image'
+  publish_image_topic: "semantic_image_debug"
+  publish_camera_info_topic: 'semantic_image_info'
+  publish_fusion_info_topic: 'semantic_image_fusion_info'
+  data_type: image
+
+  semantic_segmentation: True
+  feature_extractor: True
+  segmentation_model: 'lraspp_mobilenet_v3_large' # detectron_coco_panoptic_fpn_R_101_3x, lraspp_mobilenet_v3_large
+  show_label_legend: False
+  image_topic: "camera/rgb/image_raw"
+  camera_info_topic: "camera/depth/camera_info"
+  resize: 0.5
+
+
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/usage/plane_segmentation.html b/usage/plane_segmentation.html new file mode 100644 index 00000000..f0e3a278 --- /dev/null +++ b/usage/plane_segmentation.html @@ -0,0 +1,126 @@ + + + + + + + Plane Segmentation — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Plane Segmentation

+Convex approximation +
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/usage/plugins.html b/usage/plugins.html new file mode 100644 index 00000000..5739105d --- /dev/null +++ b/usage/plugins.html @@ -0,0 +1,486 @@ + + + + + + + Plugins — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Plugins

+

You can add your own plugin to process the elevation map and publish as a layer in GridMap message.

+

This page is structured in two parts:

+ +
+

Create a plugin

+

You can create your own plugin to process the elevation map and publish as a layer in GridMap message.

+

Let’s look at the example.

+

First, create your plugin file in elevation_mapping_cupy/script/plugins/ and save as example.py.

+
import cupy as cp
+from typing import List
+from .plugin_manager import PluginBase
+
+
+class NameOfYourPlugin(PluginBase):
+    def __init__(self, add_value:float=1.0, **kwargs):
+        super().__init__()
+        self.add_value = float(add_value)
+
+    def __call__(self,
+        elevation_map: cp.ndarray,
+        layer_names: List[str],
+        plugin_layers: cp.ndarray,
+        plugin_layer_names: List[str],
+        semantic_layers: cp.ndarray,
+        semantic_layer_names: List[str],
+        *args
+    )->cp.ndarray:
+        # Process maps here
+        # You can also use the other plugin's data through plugin_layers.
+        new_elevation = elevation_map[0] + self.add_value
+        return new_elevation
+
+
+

Then, add your plugin setting to config/plugin_config.yaml

+
example:                                      # Name of your filter
+  type: "example"                             # Specify the name of your plugin (the name of your file name).
+  enable: True                                # weather to load this plugin
+  fill_nan: True                              # Fill nans to invalid cells of elevation layer.
+  is_height_layer: True                       # If this is a height layer (such as elevation) or not (such as traversability)
+  layer_name: "example_layer"                 # The layer name.
+  extra_params:                               # This params are passed to the plugin class on initialization.
+    add_value: 2.0                            # Example param
+
+example_large:                                # You can apply same filter with different name.
+  type: "example"                             # Specify the name of your plugin (the name of your file name).
+  enable: True                                # weather to load this plugin
+  fill_nan: True                              # Fill nans to invalid cells of elevation layer.
+  is_height_layer: True                       # If this is a height layer (such as elevation) or not (such as traversability)
+  layer_name: "example_layer_large"           # The layer name.
+  extra_params:                               # This params are passed to the plugin class on initialization.
+    add_value: 100.0                          # Example param with larger value.
+
+
+

Finally, add your layer name to publishers in your config. You can create a new topic or add to existing topics.

+
plugin_example: # Topic name
+  layers: [ 'elevation', 'example_layer', 'example_layer_large' ]
+  basic_layers: [ 'example_layer' ]
+  fps: 1.0        # The plugin is called with this fps.
+
+
+
+
+

Existing plugins

+

This section lists the plugins that are already installed and available for use.

+
+

1. Min filter

+
+
+class elevation_mapping_cupy.plugins.min_filter.MinFilter(cell_n: int = 100, dilation_size: int = 5, iteration_n: int = 5, **kwargs)
+

This is a filter to fill in invalid cells with minimum values around.

+
+
Parameters:
+
    +

  • cell_n (int) – width of the elevation map.

    • +

  • dilation_size (int) – The size of the patch to search for minimum value for each iteration.

    • +

  • iteration_n (int) – The number of iteration to repeat the same filter.

    • +

  • () (**kwargs)

    • +
+
+
+
+
+__init__(cell_n: int = 100, dilation_size: int = 5, iteration_n: int = 5, **kwargs)
+
+
Parameters:
+
    +

  • plugin_params – PluginParams

    • +

  • callback (The parameter of)

    • +
+
+
+
+ +
+ +
+
+

2. Inpainting

+
+
+

3. Smooth Filter

+
+
+class elevation_mapping_cupy.plugins.smooth_filter.SmoothFilter(cell_n: int = 100, input_layer_name: str = 'elevation', **kwargs)
+

SmoothFilter is a class that applies a smoothing filter +to the elevation map. The filter is applied to the layer specified by the input_layer_name parameter. +If the specified layer is not found, the filter is applied to the elevation layer.

+
+
Parameters:
+
    +

  • cell_n (int) – The width and height of the elevation map. Default is 100.

    • +

  • input_layer_name (str) – The name of the layer to which the filter should be applied. Default is “elevation”.

    • +

  • **kwargs – Additional keyword arguments.

    • +
+
+
+
+
+__init__(cell_n: int = 100, input_layer_name: str = 'elevation', **kwargs)
+
+
Parameters:
+
    +

  • plugin_params – PluginParams

    • +

  • callback (The parameter of)

    • +
+
+
+
+ +
+ +
+
+

4. Robot centric elevation

+
+
+class elevation_mapping_cupy.plugins.robot_centric_elevation.RobotCentricElevation(cell_n: int = 100, resolution: float = 0.05, threshold: float = 0.4, use_threshold: bool = 0, **kwargs)
+

Generates an elevation map with respect to the robot frame.

+
+
Parameters:
+
    +

  • cell_n (int)

    • +

  • resolution (ruamel.yaml.scalarfloat.ScalarFloat)

    • +

  • threshold (ruamel.yaml.scalarfloat.ScalarFloat)

    • +

  • use_threshold (bool)

    • +

  • () (**kwargs)

    • +
+
+
+
+
+__init__(cell_n: int = 100, resolution: float = 0.05, threshold: float = 0.4, use_threshold: bool = 0, **kwargs)
+
+
Parameters:
+
    +

  • plugin_params – PluginParams

    • +

  • callback (The parameter of)

    • +
+
+
+
+ +
+ +
+
+

5. Semantic Filter

+
+
+class elevation_mapping_cupy.plugins.semantic_filter.SemanticFilter(cell_n: int = 100, classes: list = ['person', 'grass'], **kwargs)
+

This is a filter to create a one hot encoded map of the class probabilities.

+
+
Parameters:
+
    +

  • cell_n (int) – width and height of the elevation map.

    • +

  • classes (list) – List of classes for semantic filtering. Default is [“person”, “grass”].

    • +

  • **kwargs – Additional keyword arguments.

    • +
+
+
+
+
+__init__(cell_n: int = 100, classes: list = ['person', 'grass'], **kwargs)
+
+
Parameters:
+
    +

  • plugin_params – PluginParams

    • +

  • callback (The parameter of)

    • +
+
+
+
+ +
+
+color_map(N: int = 256, normalized: bool = False)
+

Creates a color map with N different colors.

+
+
Parameters:
+
    +

  • N (int, optional) – The number of colors in the map. Defaults to 256.

    • +

  • normalized (bool, optional) – If True, the colors are normalized to the range [0,1]. Defaults to False.

    • +
+
+
Returns:
+

The color map.

+
+
Return type:
+

np.ndarray

+
+
+
+ +
+
+transform_color()
+

Transforms the color map into a format that can be used for semantic filtering.

+
+
Returns:
+

The transformed color map.

+
+
Return type:
+

cp.ndarray

+
+
+
+ +
+
+get_layer_indices(layer_names: List[str]) → List[int]
+

Get the indices of the layers that are to be processed using regular expressions. +:param layer_names: List of layer names. +:type layer_names: List[str]

+
+
Returns:
+

List of layer indices.

+
+
Return type:
+

List[int]

+
+
+
+ +
+ +
+
+

6. Semantic traversability

+
+
+class elevation_mapping_cupy.plugins.semantic_traversability.SemanticTraversability(cell_n: int = 100, layers: list = ['traversability'], thresholds: list = [0.5], type: list = ['traversability'], **kwargs)
+

Extracts traversability and elevations from layers and generates an updated traversability that can be used by checker.

+
+
Parameters:
+
    +

  • cell_n (int) – The width and height of the elevation map.

    • +

  • layers (list) – List of layers for semantic traversability. Default is [“traversability”].

    • +

  • thresholds (list) – List of thresholds for each layer. Default is [0.5].

    • +

  • type (list) – List of types for each layer. Default is [“traversability”].

    • +

  • **kwargs – Additional keyword arguments.

    • +
+
+
+
+
+__init__(cell_n: int = 100, layers: list = ['traversability'], thresholds: list = [0.5], type: list = ['traversability'], **kwargs)
+
+
Parameters:
+
    +

  • plugin_params – PluginParams

    • +

  • callback (The parameter of)

    • +
+
+
+
+ +
+ +
+
+

7. Features PCA

+
+
+class elevation_mapping_cupy.plugins.features_pca.FeaturesPca(cell_n: int = 100, process_layer_names: List[str] = [], **kwargs)
+

This is a filter to create a pca layer of the semantic features in the map.

+
+
Parameters:
+
    +

  • cell_n (int) – width and height of the elevation map.

    • +

  • classes (ruamel.yaml.comments.CommentedSeq)

    • +

  • () (**kwargs)

    • +
+
+
+
+
+__init__(cell_n: int = 100, process_layer_names: List[str] = [], **kwargs)
+
+
Parameters:
+
    +

  • plugin_params – PluginParams

    • +

  • callback (The parameter of)

    • +
+
+
+
+ +
+
+get_layer_indices(layer_names: List[str]) → List[int]
+

Get the indices of the layers that are to be processed using regular expressions. +:param layer_names: List of layer names. +:type layer_names: List[str]

+
+
Returns:
+

List of layer indices.

+
+
Return type:
+

List[int]

+
+
+
+ +
+ +
+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/usage/semantics.html b/usage/semantics.html new file mode 100644 index 00000000..ed30a5d1 --- /dev/null +++ b/usage/semantics.html @@ -0,0 +1,205 @@ + + + + + + + Semantics — elevation_mapping_cupy documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Semantics

+

The elevation map is also able to include semantic information. +The workflow consists in two elements:

+
    +

  • semantic extension of the elevation map

    • +

  • semantic pointcloud

    • +
+
+

semantic extension of the elevation map

+

The semantics of the elevation map can be configured in the sensor parameter file. +The sensor parameter file contains all the topics the map subscribes to.

+

The channels and fusion lists are the parameters that define the semantics of the elevation map. +The channel is a list that contains the name of the semantic layers as well as the name of the channel +of the data that the elevation map node subscribes to. +The fusion list indicates the fusion algorithm type which is applied to the data to fuse the +sensor data into the map.

+

There are different fusion algorithms types:

+
    +

  • average

    • +
+
+
+
+

Takes the average of all the points that fall within the same cell and average them +and then takes a weighted average of the existing value.

+
+

use case: semantic features

+
+
    +

  • bayesian_inference:

    • +
+
+
+

Employs a gaussian bayesian inference at each iteration. Where we use the psoterior +of the previous iteration as the prior to the new iteration.

+

use case: semantic features

+
+
    +

  • class_average

    • +
+
+
+
+

Takes the average of all the points that fall within the same cell and average them +and then takes a weighted average of the existing value. If the previous value is zero

+
+

it weights the previous value with a zero weight.

+

use case: class probabilities

+
+
    +

  • class_bayesian

    • +
+
+
+

Employs a bayesian inference of a categorical distribution with a dirichlet prior. +The alpha hyperparameters of the dirichlet prior are updated at every iteration, +such that the posterior of iteration t-1 is the prior of t.

+

use case: class probabilities

+
+
    +

  • color

    • +
+
+
+

The color is subscribed as a uint32. The color of the cell is the result of the average of +all the points within that cell.

+

use case: rgb color information

+
+
+
+

Semantic pointcloud

+

Sensors do not always directly provide all semantic information. +The semantic pointcloud is a ROS node that subscribes to stereo cameras and generates a +multichannel pointcloud containing semantic information additionally to the goemteric position of +the points. +The pointcloud is also configured from the sensor_parameter file.

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file