papers AI Learner
The Github is limit! Click to go to the new site.

Improved Discrete RRT for Coordinated Multi-robot Planning

2019-01-22
Jakub Hvězda, Miroslav Kulich, Libor Přeučil

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 the 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.

Abstract (translated by Google)
URL

http://arxiv.org/abs/1901.07363

PDF

http://arxiv.org/pdf/1901.07363


Comments

Content