The path planning problem for unmanned vehicle searching over the region of interest with obstacles is investigated in this paper.The path planning problem is decomposed into the sensor deployment problem and the travelling salesman problem based on the fundamental finding that the vehicle could search the region that covered by the sensor if the vehicle pass through the position where the sensor is deployed.The positions of the sensors deployed to cover the region completely are obtained by solving the sensor deployment problem.Taking the positions of the deployed sensors as the waypoints that the vehicle has to travel through,the shortest path connecting all the waypoints can be obtained by solving the travelling salesman problem.The cooperatively coevolving particle swarm optimization algorithm with multiple update rules is newly developed for the sensor deployment problem.Numerical simulation results demonstrate the feasibility of the proposed methods.