Improved Discrete RRT for Coordinated Multi-robot Planning
This work addresses coordination for multi-robot systems, offering a practical solution for scenarios with many robots, but it is incremental as it builds on existing RRT methods.
The paper tackles the problem of finding optimal collision-free trajectories for a fleet of mobile robots by proposing an improved probabilistic approach based on the Rapidly Exploring Random Tree (RRT) algorithm for discrete environments. The result is a method that solves problems with tens of robots in seconds, though solutions are slightly worse than a state-of-the-art algorithm, but it succeeds where that algorithm fails.
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.