Multi-robot coordination using generalized social potential fields

Authors:
Russell Gayle;William Moss;Ming C. Lin;Dinesh Manocha
Affiliations:
Department of Computer Science, University of North Carolina at Chapel Hill;Department of Computer Science, University of North Carolina at Chapel Hill;Department of Computer Science, University of North Carolina at Chapel Hill;Department of Computer Science, University of North Carolina at Chapel Hill
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

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Abstract

We present a novel approach to compute collision-free paths for multiple robots subject to local coordination constraints. More specifically, given a set of robots, their initial and final configurations, and possibly some additional coordination constraints, our goal is to compute a collision-free path between the initial and final configuration that maintains the constraints. To solve this problem, our approach generalizes the social potential field method to be applicable to both convex and nonconvex polyhedra. Social potential fields are then integrated into a "physics-based motion planning" framework which uses constrained dynamics to solve the motion planning problem. Our approach is able to plan for over 200 robots while averaging about 110 ms per step in a variety of environments.