lsc_planner

This package presents an efficient multi-agent trajectory planning algorithm which generates safe trajectories in obstacle-dense environments. Our algorithm combines the advantages of both grid-based and optimization-based approaches, and generates safe, dynamically feasible trajectory without suffering from an errorneous optimization setup such as imposing infeasible collision constraints. The details can be found at the following link.

• Authors: Jungwon Park, Dabin Kim, Gyeong Chan Kim, Dahyun Oh and H. Jin Kim from LARR, Seoul National University
• Paper: Online Distributed Trajectory Planning for Quadrotor Swarm with Feasibility Guarantee using Linear Safe Corridor PDF
• Video: Youtube

1. Install

This work is implemented based on C++17. Tested in the ROS Melodic, Ubuntu 18.04

(1) Install ROS Melodic for Ubuntu 18.04 or ROS Noetic for Ubuntu 20.04 (http://wiki.ros.org/ROS/Installation, desktop-full version is recommended)

(2) Install CPLEX (https://www.ibm.com/products/ilog-cplex-optimization-studio)

(3) Install dependancies and clone packages

sudo apt-get install ros-<distro>-octomap
sudo apt-get install ros-<distro>-octomap-server
sudo apt-get install ros-<distro>-octomap-ros
sudo apt-get install ros-<distro>-dynamic-edt-3d
git clone https://github.com/qwerty35/dynamic_msgs.git
git clone https://github.com/qwerty35/graph_rviz_plugin.git
git clone https://github.com/qwerty35/lsc_planner.git

(<distro> is melodic or noetic depending on your ROS version.)

(4) Before building packages, check CMAKELIST that CPLEX_PREFIX_DIR is indicating the intallation location. For instance, if CPLEX is installed in /opt/ibm/ILOG/CPLEX_Studio201, then CPLEX_PREFIX_DIR should be:

set(CPLEX_PREFIX_DIR /opt/ibm/ILOG/CPLEX_Studio201)

(5) Build packages

cd ~/catkin_ws
catkin_make
source ~/catkin_ws/devel/setup.bash

2. Demo

source ~/catkin_ws/devel/setup.bash
roslaunch lsc_planner simulation.launch

The simulation result will be saved at lsc_planner/log.

3. Configuration

You can configure the simulation setting at the launch, mission files.

• launch/simulation.launch: Mission, octomap, parameters for algorithm
• missions/*.json: Start, goal, dynamical limit of the agent, map size

See the comments in the launch/simulation.launch and missions/readme.txt file for more details

Note: If you want to generate the mission file automatically, then use matlab script in matlab/mission_generator

4. Acknowledgment

This work is implemented based on the following packages.

(1) RVO2, RVO2-3D (https://gamma.cs.unc.edu/RVO2/downloads/)

(2) 3D-AStar-ThetaStar (https://github.com/PathPlanning/3D-AStar-ThetaStar)

(3) rapidjson (https://rapidjson.org/)

(4) openGJK (https://www.mattiamontanari.com/opengjk/)

5. Notes

(1) Numerical issue: This code may cause infeasible optimization problem due to the numerical error of dynamicEDT3D library. If you want to avoid infeasible constraints, then use alternative method in the function 'TrajPlanner::generateFeasibleSFC()' in traj_planner.cpp However, it is prone to deadlock and is too conservative.

(2) Grid based planner issue: This code is not fully tested with various maps. Grid based planner may not work with some maps.