Robot Motion planning is a computational problem that involves finding a sequence of valid configurations to move the robot from the source to the destination. Generally, it includes Path Searching and Trajectory Optimization.
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Path Searching: Based on path constraints, such as obstacles, to find the optimal sequence for the robot to travel from the source to the destination without any collisions.
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Trajectory Planning: Based on kinematics, dynamics and obstacles, it optimizes the trajectory of the motion state from the source to the destination according to the path.
This repository provides the implementation of common Motion Planning algorithms. The theory analysis can be found at motion-planning. Furthermore, we provide Python and MATLAB version.
Your stars, forks and PRs are welcome!
Tested on ubuntu 20.04 LTS with ROS Noetic.
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Install ROS (Desktop-Full suggested).
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Install git.
sudo apt install git
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Other dependence.
sudo apt install python-is-python3 \ ros-noetic-amcl \ ros-noetic-base-local-planner \ ros-noetic-map-server \ ros-noetic-move-base \ ros-noetic-navfn
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Clone the reposity.
git clone https://github.com/ai-winter/ros_motion_planning.git
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Compile the code.
NOTE: Please refer to #48 if you meet libignition dependency error.
cd ros_motion_planning/ catkin_make # or catkin build # you may need to install it by: sudo apt install python-catkin-tools
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Execute the code.
cd scripts/ ./main.sh
NOTE: Modifying launch files may not have any effect, because they are regenerated by a Python script based on
src/user_config/user_config.yaml
when you runmain.sh
. Therefore, you should modify configurations inuser_config.yaml
instead of launch files. -
Use 2D Nav Goal in RViz to select the goal.
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Moving!
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You can use the other script to shutdown them rapidly.
./killpro.sh
The overall file structure is shown below.
ros_motion_planner
├── assets
├── scripts
└── src
├── core
│ ├── global_planner
│ ├── local_planner
│ ├── curve_generation
│ └── utils
├── sim_env # simulation environment
│ ├── config
│ ├── launch
│ ├── maps
│ ├── meshes
│ ├── models
│ ├── rviz
│ ├── urdf
│ └── worlds
├── third_party
│ ├── dynamic_rviz_config
│ ├── dynamic_xml_config
│ ├── gazebo_plugins
│ └── rviz_plugins
└── user_config # user configure file
To better understand the project code, detailed interface documentation can be generated using the doxygen tool. First install doxygen and graphviz.
sudo apt-get install doxygen graphviz
Then start the doxygen and you can find the documentation in ./docs/html/index.html
.
doxygen
For more information about the project usage, please refer to the following table.
For the efficient operation of the motion planning system, we provide a series of user-friendly simulation tools that allow for on-demand selection of these lightweight repositories.
Planner | Version | Animation | Paper |
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PID | ![]() |
Mapping Single-Integrator Dynamics to Unicycle Control Commands p. 14 | |
LQR | ![]() |
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DWA | ![]() |
The Dynamic Window Approach to Collision Avoidance | |
APF | ![]() |
Real-time obstacle avoidance for manipulators and mobile robots | |
RPP | ![]() |
Regulated Pure Pursuit for Robot Path Tracking | |
TEB | |||
MPC | |||
Lattice |
Planner | Version | Animation | Paper |
---|---|---|---|
Polynomia | ![]() |
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Bezier | ![]() |
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Cubic Spline | ![]() |
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BSpline | ![]() |
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Dubins | ![]() |
On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents | |
Reeds-Shepp | ![]() |
Optimal paths for a car that goes both forwards and backwards |
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Our robot and world models are from Dataset-of-Gazebo-Worlds-Models-and-Maps and aws-robomaker-small-warehouse-world. Thanks for these open source models sincerely.
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Pedestrians in this environment are using social force model(sfm), which comes from https://github.com/robotics-upo/lightsfm.
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A ROS costmap plugin for dynamicvoronoi presented by Boris Lau.
The source code is released under GPLv3 license.
Feel free to contact us if you have any question.