Common:
~map_frame
(string
, default: map
)
SLAM map reference frame, ENU convention.
~uav_frame
(string
, default: base_link
)
UAV body frame, forward-left-up convention.
Takes raw pointcloud and does basic pre-processing, publishes 3 processed pointclouds for mapping consumption. (TODO: Some of these params likely dont need to be exposed.)
~blind
(double
, default: 0.5
)
Radius of the circle around the LiDAR to ignore (units same as LiDAR pointcloud).
~inf_bound
(double
, default: 10.0
)
? Ignore points past this boundary.
~N_SCANS
(int
, default: 6
)
Number of LIDAR scans. AVIA default is 6, VLP16 is 16.
~group_size
(int
, default: 8
)
~disA
(double
, default: 0.01
)
~disB
(double
, default: 0.1
)
~p2l_ratio
(double
, default: 225.0
)
~limit_maxmid
(double
, default: 6.25
)
~limit_midmin
(double
, default: 6.25
)
~limit_maxmin
(double
, default: 3.24
)
~jump_up_limit
(double
, default: 170.0
)
~jump_down_limit
(double
, default: 8.0
)
~cos160
(double
, default: 160.0
)
~edgea
(double
, default: 2.0
)
~edgeb
(double
, default: 0.1
)
~smallp_intersect
(double
, default: 172.5
)
~smallp_ratio
(double
, default: 1.2
)
~point_filter_num
(int
, default: 1
)
Takes processed pointcloud and produces registered pointcloud. (TODO: Some of these params likely dont need to be exposed.)
~proc_cloud_topic
(string
, default: /laser_cloud_flat
)
Topic to subscribe, produced by feature extract for use in map creation.
~reg_cloud_topic
(string
, default: /cloud_registered
)
Topic to publish resulting registered cloud.
~imu_topic
(string
, default: /mavros/imu/data
)
Topic to subscribe for IMU data.
~odom_topic
(string
, default: /mavros/odometry/out
)
Topic to publish odom data registered to map.
~map_file_path
(string
, default:
)
~max_iteration
(int
, default: 10
)
~dense_map_enable
(bool
, default: true
)
~fov_degree
(double
, default: 75.0
)
~filter_size_corner
(double
, default: 0.3
)
~filter_size_surf
(double
, default: 0.2
)
~filter_size_map
(double
, default: 0.2
)
~cube_side_length
(double
, default: 20.0
)
Plans paths through map produced by the SLAM node (FAST LIO package), where the map is in pointcloud form. Essentially a wrapper for path-searching node.
~cloud_topic
(string
, default: /cloud_registered
)
Referenced pointcloud, generated by SLAM node.
~odom_topic
(string
, default: /mavros/odometry/out
)
Topic to publish odometry.
Uses kinodynamic A* search. An instance of path search is created by the path planning node.
~max_tau
(double
, default: 0.6
)
~init_max_tau
(double
, default: 0.8
)
~max_vel
(double
, default: 2.0
)
~max_acc
(double
, default: 2.0
)
~w_time
(double
, default: 10.0
)
~horizon
(double
, default: 100.0
)
~resolution_astar
(double
, default: 0.1
)
~time_resolution
(double
, default: 0.8
)
~lambda_heu
(double
, default: 5.0
)
~vel_margin
(double
, default: 0.0
)
~allocate_num
(int
, default: 100000
)
~check_num
(int
, default: 1
)
~optimistic
(bool
, default: true
)
This repo was forked from https://github.com/hku-mars/dyn_small_obs_avoidance.git which states the following: This repository is used for UAV dynamic small obstacles avoidance. It is a complete system for lidar-based UAV, including FAST-LIO slam, time-accumulated KD-Tree mapping and kinodynamic A* search modules. It is able to avoid dynamic small obstacles (down to 20mm diameter bars) by running at 50Hz.
Related paper: "Avoiding dynamic small obstacles with onboard sensing and computating on aerial robots", available on arxiv now https://arxiv.org/abs/2103.00406.
Related video: https://youtu.be/pBHbQ_J1Qhc
Thanks for FAST-PLANNER(Zhou, Boyu and Gao, Fei and Wang, Luqi and Liu, Chuhao and Shen, Shaojie. Robust and efficient quadrotor trajectory generation for fast autonomous flight), FAST-PLANNER.