Multi-robot coordination using switching of methods for deriving equilibrium in game theory

The study of a Multi-Agent System using multiple autonomous robots has recently attracted much attention. With the problem of target tracking as a typical case study, multiple autonomous robots decide their own actions to achieve the whole task which is tracking target. Each autonomous robot´s action influences each other, so, an action decision in coordination with other robots and the environment is needed to achieve the whole task effectively. The game theory is a major method realizing a coordinated action decision. The game theory mathematically deals with a multi-agent environment influencing each other as a game situation. The conventional methods model one of the target tracking as a n-person general-sum game, and use the noncooperative Nash equilibrium theory of non-cooperative games and the semi-cooperative Stackelberg equilibrium. The semi-cooperative Stackelberg equilibrium may obtain better control performance than the non-cooperative Nash equilibrium, but requires the communication among robots. In this study, we propose switching of methods in the equilibrium derivation both the non-cooperative Nash equilibrium and the semi-cooperative Stackelberg equilibrium in a coordination algorithm for the target tracking. In the simulation, our proposed method achieves coordination in less connection than the method using the semi-cooperative Stackelberg equilibrium at all times. Furthermore, the proposed method shows better control performance than the non-cooperative Nash equilibrium.