A GA based combinatorial auction algorithm for multi-robot cooperative hunting

In order to improve the hunting efficiency of multi-robot cooperative hunting in complicated environment: multi-target and dynamic continues surrounding, a combinatorial auction model based on genetic algorithm (GACA) was presented in this paper. The model adopted genetic algorithm to solve the winner determination problem in combinatorial auction. We also compared the combinatorial auction model based task allocation method with the traditional single item auction model in solving dynamic and complex task allocation problem in multi-robot cooperation. The simulation experiments were conducted in a self-developed visible multi-robot simulation platform, OpenSim, and the results showed the whole process of hunting was very smooth, and the cost time cost by our algorithm was much shorter than the compared method.