Path Planning for Multi-Vehicle Formation with Obstacles via Joint Grid Network and Improve Particle Swarm Optimization

This paper investigates the path planning problem for multiple vehicles formation in multiple obstacles environment. The kinematics model of the intelligent small robot vehicle (ISRV) is proposed by mechanical analysis. In order to remove the deadlock phenomenon during the path planning, a joint grid network and improved particle swarm optimization algorithm for path planning of multiple vehicles is proposed. The long path in the whole working environment with multiple obstacles is divided into multi-segment continuous short paths by the grid network. Then, the improved particle swarm optimization (IPSO) algorithm is used to search for the optimal path in the short paths for the mobile vehicles formation. Finally, some experiments are performed to demonstrate the effectiveness of the proposed path planning algorithm for multi-vehicle formation.