mrca-mav's Introduction

Model Predictive Control for Multi-MAV Collision Avoidance in Dynamic Environments

This repository contains the code for the paper:

Chance-Constrained Collision Avoidance for MAVs in Dynamic Environments
Hai Zhu, and Javier Alonso-Mora
Published in [RA-L + ICRA 2019]. You can find the full-text paper here.

Please click in the image to see our video:

If you find this code useful in your research then please cite:

@article{Zhu2019RAL,
    title = {{Chance-Constrained Collision Avoidance for MAVs in Dynamic Environments}},
    author = {Zhu, Hai and Alonso-Mora, Javier},
    journal = {IEEE Robotics and Automation Letters},
    number = {2},
    volume = {4},
    pages = {776--783},
    publisher = {IEEE},
    year = {2019}
}

The authors would like to thank Embotech for providing a license of the FORCES PRO software.

Software Requirements

ROS installation
Ubuntu 16.04 (or 18.04)
MATLAB R2017b (or R2019b) with the Robotics System Toolbox
FORCES PRO software

Installation instructions

This set of instructions have been tested for Ubuntu 16.04 with ROS-Kinetic and MATLAB R2017b, and Ubuntu 18.04 with ROS-Melodic and MATLAB R2019b.

Running Simulations

Problem Set Up
1. Launch a MATLAB instance and open initialize.m
2. Setup the number of drones and dynamic obstacles
3. Set cfg.modeSim as 1
4. Set getNewSolver as 1 if a new mpc solver is required to be generated
Open Visualization
1. Start a MATLAB instance
2. Run the script run_visual.m
Open the Controller
1. Start another MATLAB instance
2. Run the script run_main_basic.m

Running Experiments

The code supports running experiments using the Parrot Bebop 2 quadrotors. Real-time state estimation of the quadrotors and moving obstacles are required. The following packages will be useful if you want to set up real-world experiments: