Human dense avoidance based on a coverage control through robots

In this paper, we propose an efficient method for human dense avoidance based on a coverage control. Our motivation is to avoid crowding in public facilities such as stations and government offices, and human dense in the current situation of COVID-19 from system and control theory. In this paper, humans and robots are modeled as heterogeneous and homogeneous agents, respectively, which make decisions based on their local information. We suppose a dense situation caused by the rendezvous among humans due to their own inherent dynamics. As a main result, we propose a coverage control for a distributed movement of multiple humans. We also characterize the stationary point analytically in terms of the gains that describe a strength of the interconnection of the agents, and the centers of the Voronoi regions related to the agents. Moreover, we verify the meaning of the characterization from an engineering viewpoint of the dense avoidance. Finally, we show the efficiency of the method based on a numerical simulation.