Skip to content
forked from WPI-AIM/ambf

Asynchronous Multi-Body Framework

Notifications You must be signed in to change notification settings

JackHaoyingZhou/ambf

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Asynchronous Multi-Body Framework (AMBF)

Author: Adnan Munawar (amunawar@wpi.edu)

Build Status

ambf-2.0

Please checkout the discussions tab for questions, suggestions, and connecting with the community.

2. Wiki:

Please check out the Wiki for in-depth details about AMBF, its components, examples, and concepts. You can also check out the video below for a brief rundown of some of the features of AMBF.

AMBF Simulator

3. Description:

This multi-body framework offers a real-time dynamic simulation of robots, free bodies, and multi-link puzzles coupled with real-time haptic interaction via several haptic devices (CHAI-3D) (including dVRK Manipulators and Razer Hydras). It also provides a Python client for training NN and RL Agents on real-time data with the simulation in the loop. This framework is built around several external tools that include an extended version of CHAI-3D (developed alongside AMBF), BULLET-Physics, Open-GL, GLFW, yaml-cpp, pyyaml, and Eigen to name a few. Each external library has its license that can be found in the corresponding subfolder.

4. Featured Projects:

These are some example projects that are developed on/using AMBF. Please click on the project title to navigate to the project webpage.

drilling_matcap.mp4

The bone drilling simulator also provides stereoscopic view of supported Virtual Reality (VR) Head Mounted Displays (HMDs):

Barrel.Roll.Distortion.mp4
surgical_robotics_half.mp4
space_robotics_half.mp4

5. Usage:

5.1 Tested Platforms:

AMBF has been tested on Ubuntu 16.04, Ubuntu 18.04 and Ubuntu 20.04. We need a few extra steps on Ubuntu 14.04, please create an issue if you would like to get instructions for that.

Even though it is recommended to use Linux for the full feature set of AMBF using ROS, AMBF has been tested on MacOS Maverick and MacOS Mojave without ROS support.

5.2 Building:

5.2.1 Linux (Ubuntu 16.04, 18.04, 20.04):

Install the following dependencies if not present:

sudo apt install libasound2-dev libgl1-mesa-dev xorg-dev

Optional but recommended: Install the appropriate ROS 1 version for your specific Linux distribution based on the instructions here http://wiki.ros.org/ROS/Installation. Source the ROS installation by following the instructions in Section 1.5 Environment Setup here (http://wiki.ros.org/noetic/Installation/Ubuntu). Note: Change the ROS version based on which ROS you have installed.

Now we can proceed to build AMBF:

cd ~
git clone https://github.com/WPI-AIM/ambf.git
cd ambf && mkdir build
cd build
cmake ..
make

Optional but recommended (If building with ROS support): Source the correct folder to achieve system-wide availability of AMBF ROS modules.

cd ~/ambf/build/
source ./devel/setup.bash

You can also permanently add the install location in your ~/.bashrc with the following command:

echo "source ~/ambf/build/devel/setup.bash" >> ~/.bashrc
# Then either reload the terminal or run `. ~/.bashrc` for the changes to take effect

Creating an Alias: AMBF can be executed by navigating to the ambf/bin/<os> directory (i.e. cd ambf/bin/<os>) and typing ./ambf_simulator. For Linux, this may be ambf/bin/lin-x86_64 and on MacOS it may be ambf/bin/mac-x86_64. To execute ambf_simulator without having to be in the ambf/bin/<os> directory, one can set an alias at the end of the ~/.bashrc file.

# Open the ~/.bashrc file in a text editor
# At the end of the file add
alias ambf_simulator=~/ambf/bin/lin-x86_64/ambf_simulator # Replace lin-x86_64 with your OS.
# Save and close the file and reload by either relaunching the terminal or typing 
. ~/.bashrc

With the alias set, ambf_simulator can be executed from a terminal from any location. Please check that by opening a new terminal and typing

ambf_simulator

Working with Multiple ROS Workspaces: You may notice that if you have ROS packages in a Catkin workspace (e.g. ~/your_catkin_ws) then sourcing AMBF unsources that your_catkin_ws (i.e. the packages in your_catkin_ws are no longer accessible in the terminal) and vice-versa. This happens because the workspaces (your_catkin_ws and ambf/build/devel) are not properly overlaid. You can read more about workspace overlaying here: Overlaying with catkin workspaces.

In summary, if you wish to use AMBF's ROS packages (e.g. ambf_client or ambf_msgs) within a separate ROS package (e.g., your_catkin_ws), it is recommended to overlay the Catkin workspaces (other Catkin workspaces with AMBF):

  1. Ensure that AMBF is sourced in your terminal.
  2. Ensure your_catkin_ws has not been built (catkin clean and/or remove build and devel if it has been built).
  3. Build your_catkin_ws.

Under the hood this will do a caktin workspace overlay, which will make sure AMBF is sourced whenever you source your_catkin_ws and that sourcing your_catkin_ws does not make the AMBF packages "unsource"/get overwritten in the environment variables.

5.2.2 Mac OS

If you don't have Boost libraries, you will need to install them as follows

  1. Install Xcode from App Store
  2. Install command-line tools by running this in the terminal xcode-select --install
  3. Install Homebrew view running this in terminal /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
  4. Install boost by running the following in the terminal brew install boost

To build the framework (Linux and Mac-OS):

cd ~
git clone https://github.com/WPI-AIM/ambf.git
cd ambf && mkdir build
cd build
cmake ..
make

5.3 Running AMBF:

Having completed the steps above running AMBF is easy.

On Linux OS, open a terminal and run roscore.

roscore

Then depending on what OS you're using simply follow the commands below in a new terminal:

ambf_simulator

5.4 Launching Specific AMBF Description Format (ADF) Files:

There are two ways to launch an ADF file:

  1. Using the integer index of the filename specified in the launch file
  2. Providing the explicit filename(s).
5.4.1 Using the Integer Index in the launch file

The -l command-line argument can be used to launch a specific ADF file at launch using indexing. The ADF files are defined in ambf_models/descriptions/launch.yaml and are commented with indices for ease of identification. By default, launching the simulator without the -l command line argument loads the first 1 ADF file defined in the (launch.yaml)[./ambf_models/descriptions/launch.yaml]. To launch a specific ADF file you can use the -l flag with its integer index as follows:

ambf_simulator -l 4

This command will launch the 4th ADF file defined in the launch.yaml file. To launch multiple ADF files, you can use a comma-separated list (without spaces in between) of integers indices e.g.ambf_simulator -l 1,6,10. This in turn would load the ADF files defined at 1, 6, and the 10th index in the launch.yaml file.

5.4.2 Providing the fully qualified filename

The second option is to use the -a flag. For example, if one has an AMBF description file in the home directory /users/potato/tests/robot.yaml, this file can be launched directly as follows

ambf_simulator -a /users/potato/tests/robot.yaml

Similarly, as is the case with the -l flag, multiple filenames can be launched by comma-separated values. E.g.

ambf_simulator -a /users/potato/tests/robot.yaml,/users/potato/tests/car.yaml

Lastly, the -l and -a flags can be used together to launch some files based on the index and some based on the filenames.

5.4.3 Note:

The entry point to AMBF is via the launch file located in ambf/ambf_models/descriptions/launch.yaml. This is a meta-data file that contains filepaths of a world description file, an input-device file, and scene-data files (that may define a group of links, joints, sensors, actuators, cameras, lights, etc.).

6 Creating custom AMBF Description Format (ADF) Files:

Robots and scene data are defined using the ADF files. These can be created either by hand or by using the blender-ambf addon. Please refer to its documentation for loading and creating ADF files in Blender.

7 Interacting with the Robots/Bodies in AMBF:

There are multiple ways of interacting with the bodies in the simulator. If you are using Linux, the provided Python client offers a convenient user interface and robust API.

For the full feature set of the AMBF, it is advised that you install it on Linux (Ubuntu) 16, 17, or 18. Other variants might be supported but have not yet been tested.

7.1 The AMBF Python Client

The simplest way to interact with bodies in the AMBF is by using the high-speed Asynchronous Communication Interface that is implemented via ROS-topics in the AMBF Framework Library. One can use either C++ or Python for this purpose. A convenient Python Client is provided for easy interaction.

Start AMBF with the desired ADF file.

Then, in your Python application

# Import the Client from ambf_comm package
# You might have to do: pip install gym
from ambf_client import Client
import time

# Create an instance of the client
_client = Client()

# Connect the client which in turn creates callable objects from ROS topics
# and initiates a shared pool of threads for bi-directional communication
_client.connect()

# You can print the names of objects found
print(_client.get_obj_names())

# Lets say from the list of printed names, we want to get the
# handle to an object named "Torus"
torus_obj = _client.get_obj_handle('Torus')

# Now you can use the torus_obj to set and get its position, rotation,
# Pose etc. If the object has joints, you can also control them
# in either position control mode or open-loop effort mode. You can even mix and
# match the joints commands
torus_obj.set_pos(0, 0, 0) # Set the XYZ Pos in obj's World frame
torus_obj.set_rpy(1.5, 0.7, .0) # Set the Fixed RPY in World frame
time.sleep(5) # Sleep for a while to see the effect of the command before moving on

# Other methods to control the obj position include
# torus_obj.set_pose(pose_cmd) # Where pose_cmd is of type Geometry_msgs/Pose
# torus_obj.set_rot(quaternion) # Where quaternion is a list in the order of [qx, qy, qz, qw]
# Finally all the position control params can be controlled in a single method call
# torus_obj.pose_command(px, py, pz, roll, pitch, yaw, *jnt_cmds)

# We can just as easily get the pose information of the obj
cur_pos = torus_obj.get_pos() # xyx position in World frame
cur_rot = torus_obj.get_rot() # Quaternion in World frame
cur_rpy = torus_obj.get_rpy() # Fixed RPY in World frame

# Similarly you can directly control the wrench acting on the obj by
# The key difference is that it's the user's job to update the forces
# and torques in a loop otherwise the wrench is cleared after an internal
# watchdog timer expires if a new command is not set. This is for safety
# reasons where a user shouldn't set a wrench and then forget about it.
for i in range(0, 5000):
    torus_obj.set_force(5, -5, 10) # Set the force in the World frame
    torus_obj.set_torque(0, 0, 0.8) # Set the torque in the World frame
    time.sleep(0.001) # Sleep for a while to see the effect of the command before moving on

# Similar to the pose_command, one can assign the force in a single method call
# torus_obj.wrench_command(fx, fy, fz, nx, ny, nz) in the World frame

# We can get the number of children and joints connected to this body as
num_joints = torus_obj.get_num_joints() # Get the number of joints of this object
children_names = torus_obj.get_children_names() # Get a list of children's names belonging to this obj

print(num_joints)
print(children_names)

# If the obj has some joints, we can control them as follows
if num_joints > 1:
    torus_obj.set_joint_pos(0, 0.5) # The joints at idx 0 to 0.5 Radian
    torus_obj.set_joint_effort(1, 5) # Set the effort of the joint at idx 1 to 5 Nm
    time.sleep(2) # Sleep for a while to see the effect of the command before moving on


# Lastly to cleanup
_client.clean_up()

8 Raven and DVRK Kinematics Controller Client

See here for more information.

9 AMBF Network Setup:

To subscribe and publish data using AMBF over multiple machines, the following steps would need to be followed:

  1. Check the connectivity between the machines (example: using ssh and ping)
  2. Edit the /etc/hosts and add the hostnames of the machines, so that the machines can find each other over the network (example: similar to Adding hostname to /etc/hosts)
  3. Set the ROS environment variable in the local machine to the host using export ROS_MASTER_URI=http://hostIPaddress:11311 (ex: export ROS_MASTER_URI=http://112.115.256.121:11311)
  4. Now you should be able to send and receive ROS messages over the two machines and control AMBF.
  5. If you face any firewall issues or if you are unable to receive/publish any ROS topics over the two machines, follow the next step.
  6. Open a terminal and type the command: sudo apt-get install gufw
  7. Next type sudo gufw (type the password when prompted) and ensure both the Incoming and Outgoing traffic is allowed.

10 Docker with visualization

Please follow these instructions.

Citation

If this work is helpful for your research, please use the following reference for citation:

@INPROCEEDINGS{8968568,
author={A. {Munawar} and Y. {Wang} and R. {Gondokaryono} and G. S. {Fischer}},
booktitle={2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
title={A Real-Time Dynamic Simulator and an Associated Front-End Representation Format for Simulating Complex Robots and Environments},
year={2019},
volume={},
number={},
pages={1875-1882},
keywords={},
doi={10.1109/IROS40897.2019.8968568},
ISSN={2153-0858},
month={Nov},}

About

Asynchronous Multi-Body Framework

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • C++ 76.6%
  • Python 18.0%
  • CMake 4.2%
  • GLSL 0.6%
  • C 0.4%
  • Dockerfile 0.1%
  • Shell 0.1%