Improved Discrete RRT for Coordinated Multi-robot Planning

Jakub Hvězda, Miroslav Kulich, Libor Přeučil

2018

Abstract

This paper addresses the problem of coordination of a fleet of mobile robots – the problem of finding an optimal set of collision-free trajectories for individual robots in the fleet. Many approaches have been introduced during last decades, but a minority of them is practically applicable, i.e. fast, producing near-optimal solutions, and complete. We propose a novel probabilistic approach based on the Rapidly Exploring Random Tree algorithm (RRT) by significantly improving its multi-robot variant for discrete environments. The presented experimental results show that the proposed approach is fast enough to solve problems with tens of robots in seconds. Although the solutions generated by the approach are slightly worse than one of the best state-of-the-art algorithms presented in (ter Mors et al., 2010), it solves problems where ter Mors’s algorithm fails.

Paper Citation

in Harvard Style

Hvězda J. and Přeučil L. (2018). Improved Discrete RRT for Coordinated Multi-robot Planning.In Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-321-6, pages 171-179. DOI: 10.5220/0006865901710179

in Bibtex Style

@conference{icinco18,
author={Jakub Hvězda and Libor Přeučil},
title={Improved Discrete RRT for Coordinated Multi-robot Planning},
booktitle={Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2018},
pages={171-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006865901710179},
isbn={978-989-758-321-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Improved Discrete RRT for Coordinated Multi-robot Planning
SN - 978-989-758-321-6
AU - Hvězda J.
AU - Přeučil L.
PY - 2018
SP - 171
EP - 179
DO - 10.5220/0006865901710179