Distributed Dynamic Coverage and Avoidance Control Under Anisotropic Sensing

This paper addresses dynamic coverage in multiagent systems along with certain safety and convergence guarantees. We consider anisotropic sensing for each agent, realized as conical sensing footprints and coverage functionals. This modeling results in asymmetric (directed) interactions among agents, in the sense that connected agents may either all be in the same mode (avoidance) or in different modes (avoidance and coverage). We build local and global coverage strategies which force the agents to collaboratively search a domain of interest, and avoidance strategies which waive the assumption on only pairwise interactions among agents. The proposed approach is suitable for surveillance applications where agents explore and gather sufficient information about an environment. The efficacy of the approach is demonstrated through simulation results.