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The problem of multi-robot coordination and cooperation has drawn great interest in recent years [1]. Generally speaking, for a given task, utilizing more than one robot may enhance the quality of the solution. Furthermore, many inherently distributed tasks must require a distributed solution. However, if the robots are not properly organized, the interference among them will block the task. Many challenging issues should be considered carefully. In this paper, we conduct our research in the context of multi-robot hunting. The hunting task concerning mobile robots and its target to be hunted is a particular challenge due to the nature of unknown and irregular motion of the target. In order to coordinate the motion of multiple mobile robots to capture or enclose a target, a novel feedback-control law [2], linear autonomous system [3] and Multiple Objective Behavior Coordination [4] have been used. Other related works including pursuit game [5][7], whose environments are usually modeled in grid. In this chapter, we choose non-grid environments where each robot with a limited visual field moves in any collision-free direction. This chapter considers a typical hunting task where multiple mobile robots (pursuers) cooperatively hunt an invader with certain intelligence in unknown environments. After the invader is found, its position information is broadcasted. If each robot knows where other robots are, it may take action from the group’s perspective. However, this will generate a communication burden that is too heavy to be practical. An approach where no positions of the robots are exchanged must be pursued. With less information, what action should the individual robot take? In this paper, an approach called Cooperative Local Interaction (CLI) is proposed to achieve cooperative hunting. This chapter is organized as follows. Section 2 describes CLI approach where the hunting task is divided into four states and the detailed design in each state is given. In section III, the motion strategies for the invader are designed. Simulations are conducted in section IV and section V concludes the chapter.

Cooperative Hunting by Multiple Mobile Robots Based on Local Interaction