Collective Motion Planning for a Group of Robots Using Intermittent Diffusion

Christina Frederick, Magnus Egerstedt, Haomin Zhou

Abstract: In this work we establish a simple yet effective strategy, based on intermittent diffusion, for enabling a group of robots to accomplish complex tasks, shape formation and assembly. We demonstrate the feasibility of this approach and rigorously prove collision avoidance and convergence properties of the proposed algorithms.