Multi-robot Coordination and Planning

Russell Gayle, William Moss, Ming C. Lin, Dinesh Manocha

{rgayle,wmoss,lin,dm}@cs.unc.edu



Multiple robots in a guarding and escorting scenario. 35 aggressive agents (in red) are trying to reach an important robot (in green). The darker robots are attempting to stay in a guarding formation to protect the important robot, while escorting it across an environment. Our social force model allows the aggressive robots to move toward the important robot while also avoiding collisions with each other.
 



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 non-convex 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.
Paper
Multi-robot Coordination Using Generalized Social Potential Fields
Russell Gayle, William Moss, Ming C. Lin, Dinesh Manocha
IEEE International Conference on Robotics and Automation (ICRA), 2009

Paper


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Acknowledgements
This work was supported in part by a Department of Energy High-Performance Computer Science Fellowship administered by the Krell Institute, ARO, NSF, RDECOM, and Intel Corporation.

DOE-HPCSF ARO NSF ONR DARPA
GAMMA
UNC-CS GAMMA Group
Department of Computer Science
Campus Box 3175
UNC-Chapel Hill
Chapel Hill, NC 27599-3175