Abstract
A novel self-organizing approach to cooperative hunting by swarm robotic systems is put forward. Firstly, an individual autonomous motion planning is presented, and the cooperative hunting behaviors are mathematically described. According to decomposition of hunting behaviors, the loose-preference rule is established for the individuals to form the ideal hunting formation during the self-organizing process by the interaction between the target and individuals. Then, we employ the proposed rule to design the autonomous motion controller of the individuals. Finally, the stability of self-organizing system is analyzed by Lyapunov stability criteria. Simulations and experiments demonstrate the feasibility and effectiveness of the proposed approach to cooperative hunting by swarm robotic systems.
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