Multi-robot Trajectory Planner

This repository contains the code for the paper:

Efficient Trajectory Planning for Multiple Non-holonomic Mobile Robots via Prioritized Trajectory Optimization

Authors: Juncheng Li, Maopeng Ran, and Lihua Xie from Nanyang Technological University.

Accepted in IEEE Robotics and Automation Letters (RA-L). You can find the full-text paper here.

This paper proposes an efficient trajectory planning approach that generates safe, dynamically feasible and near-optimal trajectories for multiple non-holonomic mobile robots in obstacle-rich environments.

Please click in the image to see our video:

1. Software Requirements

• Ubuntu 16.04
• ROS Kinetic
• Octomap
• Ipopt

2. Installation instructions

(1) Install ROS Kinetic for Ubuntu 16.04

Follow ROS Installation

(2) Install Ipopt solver

Follow Ipopt Installation

(3) Install dependencies

sudo apt-get install ros-kinetic-octomap*
sudo apt-get install ros-kinetic-dynamic-edt-3d
sudo apt-get install cppad

(4) Build:

cd ~/catkin_ws/src
git clone https://github.com/LIJUNCHENG001/multi_robot_traj_planner.git
cd ../ && catkin_make
source ~/catkin_ws/devel/setup.bash

2. Run Simulations

Warehouse

roslaunch multi_robot_traj_planner prioritized_plan_warehouse.launch 

Environment with random obstacles

roslaunch multi_robot_traj_planner prioritized_plan_random_env.launch

3. Simulation Configuration

You can configure the simulation settings in the launch files.

(1) Environment: The simulation environment is selected by argument 'replay_map'. The build-in maps are located in /mapfile.

(2) Mission: The mission of the robots is selected by argument 'mission'. The build-in mission files are located in /missions.

(3) Priority Assignment: A prioritized trajectory optimization method is applied to improve the computation efficiency. If argument 'plan_random_group' is true, the priority of the robots is randomly assigned. Otherwise, a novel priority assignment method proposed in the paper is applied.

(4) Backward Movement: If argument 'backward_enable' is true, the robots are able to move backward. Otherwise, the robots can only have forward speed.

4. Acknowledgements

Our implementation is built on top of libMultiRobotPlanning and swarm_simulator. We thank Wolfgang Hönig and Jungwon Park for their great work.