A potential field-based PSO approach to multi-robot cooperation for target search and hunting

The control design of target search and hunting using multi-robot remains a challenge in recent years. In this paper, we propose a control algorithm of multi-robot for target search and hunting inspired by potential field-based particle swarm optimization (PPSO). Firstly, a potential field function is established according to the initial positions of the obstacles, un-search area and targets. Then, the fitness function of PSO's (particle swarm optimization) is determined by the potential function of the work area. Lastly, multi-robot start performing target search and hunting missions driven by the proposed PPSO algorithm. Simulation results demonstrate that the PPSO algorithm is applicable and feasible for multi-robot cooperation to search and hunting targets. Compared with other commonly used methods for control of multi-robot, simulation results indicate that the PPSO algorithm has more stability and higher efficiency.