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.