Hunting in Unknown Environments with Dynamic Deforming Obstacles by Swarm Robots

In this paper, a self-organizing method, which is based on a simplified virtual-force model, is proposed for nonholonomic mobile swarm robots hunting in unknown environments. First, the motion models for the hunted target in unknown cluttered environments are designed. Next, through the decomposition of hunting behaviors under cluttered environments, a simplified virtual-force model is formed. Then, based on the virtual-force model, a control method is designed for swarm robots following motions of barriers and the target. The method only needs the location information of the target and two nearest neighbors, so it is easy to be calculated and realized. After that, the stability of the hunting system is analyzed and the control parameter ranges are achieved. Simulation results for different situations and comparative analyses demonstrate that the proposed hunting method has good performance of obstacles avoidance and flexibility.