Car-like-Robotic-swarm
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Source code for the decentralized car-like robotic swarm
Decentralized Car-Like Robotic Swarm
0. Overview
Code in this repo is about the decentralized car-like robotic swarm in a simulation environment. Due to the authority, we replace the Carla map with a simple environment, where the MPC controller is also removed.
Related Paper:
Decentralized Planning for Car-Like Robotic Swarm in Cluttered Environments, Changjia Ma, Zhichao Han, Tingrui Zhang, Jingping Wang, Long Xu, Chengyang Li, Chao Xu and Fei Gao, Accepted by IROS 2023.
The video link: youtube and bilibili.
1. Setup
All the Simulations are conducted in the Linux environment on a PC equipped with an Intel Core i7-10700 CPU and a GeForce RTX 3070 GPU.
Our software is developed and tested in Ubuntu 20.04 with ROS installed.
Attention! Map generator in this source code requires a higher version of python3, hence we do not recommend using Ubuntu 18 since the default version of python is python2.
2. Build on ROS
- Create an empty new workspace and clone this repository to your workspace:
git clone https://github.com/ZJU-FAST-Lab/Car-like-Robotic-swarm.git
cd Car-like-Robotic-swarm
- Compile it.
catkin_make -DCMAKE_BUILD_TYPE=Release
Attention! When compiling, be sure to use release mode!(Just follow the above command)
3. Run
source devel/setup.bash
Then, run the command:
roslaunch traj_planner swarm.launch
Wait for about 2 seconds until the global map comes out.
Then, you can click the 2D Nav Goal at anywhere in RVIZ to trigger the planning.
Here is an example:
Tip: We recommend developers to use rosmon to replace the roslaunch since rosmon is more friendly to mulit-robot systems.
Please refer to swarm formation for more details of rosmon.
4. Licence
The source code is released under GPLv3 license.
5. Acknowledgement
The trajectory representation is modified from MINCO.
For a more detailed version of car-like robot planning, please see Dftpav.
6. Maintaince
For any technical issue, please contact Changjia Ma([email protected]).
For commercial inquiries, please contact Fei GAO ([email protected]).