Social potentials for scalable multi-robot formations

Abstract

Potential function approaches to robot navigation provide an elegant paradigm for expressing multiple constraints and goals in mobile robot navigation problems. As an example, a simple reactive navigation strategy can be generated by combining repulsion from obstacles with attraction to a goal. Advantages of this approach can also be extended to multirobot teams. In this paper we present a new class of potential functions for multiple robots that enables homogeneous large-scale robot teams to arrange themselves in geometric formations while navigating to a goal location through an obstacle field. The approach is inspired by the way molecules "snap" into place as they form crystals; the robots are drawn to particular "attachment sites" positioned with respect to other robots. We refer to these potential functions as "social potentials" because they are constructed with respect to other agents. Initial results, generated in simulation, illustrate the viability of the approach.