In order to improve the coverage efficiency and adaptability of multi-robot collaboration search in complex environments,a multi-robot path planning strategy for collaborative full-coverage search is proposed.Firstly,the Cooperative Coevolving Particle Swarm Optimization (CCPSO2)is used for sensor deployment in the target area.Secondly,the improved K-means method is used to cluster sensor deployment points,so as to achieve effective task area division.Finally,the deployed sensor location is taken as the waypoint to solve the Traveling Salesman Problem (TSP),and the enclosed path of each robot is obtained,so as to realize collaborative full-coverage search.The experimental results show that the proposed method can obtain a more evenly-distributed coverage path for each robot while ensuring good obstacle avoidance and minimizing the coverage period,which realizes effective collaborative full-coverage search of multiple robots,and can effectively adapt to the external complex environments with good robustness.