ORCA-RRT*

Paper

Finding Coordinated Paths for Multiple Holonomic Agents in 2-d Polygonal Environment

Appears in: Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems AAMAS 2014, May 5-9, 2014, Paris, France

Authors

Pavel Janovsky (pavel.janovsky at agents.fel.cvut.cz), Michal Cap (michal.cap at agents.fel.cvut.cz), Jiri Vokrinek (jiri.vokrinek at agents.fel.cvut.cz)

Abstract

Avoiding collisions is one of the vital tasks for systems of autonomous mobile agents. We focus on the problem of finding continuous coordinated paths for multiple mobile disc agents in a 2-d environment with polygonal obstacles. The problem is PSPACE-hard, with the state space growing exponentially in the number of agents. Therefore, the state of the art methods include mainly reactive techniques and sampling-based iterative algorithms.

We compare the performance of a widely-used reactive method ORCA [1] with three variants of a popular planning algorithm RRT* [2] applied to multi-agent path planning and find that an algorithm combining reactive collision avoidance and RRT* planning, which we call ORCA-RRT* can be used to solve instances that are out of the reach of either of the techniques. We experimentally show that: 1) the reactive part of the algorithm can efficiently solve many multi-agent path finding problems involving large number of agents, for which RRT* algorithm is often unable to find a solution in limited time and 2) the planning component of the algorithm is able to solve many instances containing local minima, where reactive techniques typically fail.

(a) ORCA-RRT* (b) ORCA Figure 1: Improvement of the reactive technique ORCA	Figure 2: Example problem instance
Figure 3: Success Rate of the compared algorithms	Figure 4: Problem Environments

References

[1] J. van den Berg, S. J. Guy, M. Lin and D. Manocha. Reciprocal n-body collision avoidance. 2011.

[2] Karaman and Frazzoli. Sampling-based algorithms for optimal motion planning. I. J. Robotic Res., 20(5):846-894, 2011.