Multi-robot target hunting based on dynamic adjustment auction algorithm

Abstract

A combination of dynamic adjustment method and multi-robot task allocation auction algorithm is presented, which is an efficient algorithm to solve task allocation problem of multi-robot cooperative hunting. Firstly, this paper optimizes the auction algorithm which can improve the coordination and negotiation performance in multi-robot system and greatly reduce the amount of communication and computation. Secondly, the concept of strengthen learning is introduced into the auction algorithm to facilitate the dynamic task adjustment after the initially allocation which can adapt to the dynamic surroundings well. At last, experimental results show that the proposed algorithm is effective and the performance is better than other similar tasks allocation algorithms.