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.