Joint grid network and improved particle swarm optimization for path planning of mobile robot

This paper deals with the optimal path planning problem for mobile robot which are drove in obstacle environment. Specially, we aim at solving the deadlock problem using grid network and improved particle swarm optimization algorithm. The proposed method is different from traditional particle swarm optimization method, which generally has high-computational complexity and local deadlock. Instead, we utilize the integrated grid network and improved particle swarm optimization algorithm. By the grid network, the long path in the whole workspace with obstacles is divided into multi-segment continuous short paths. The improved particle swarm optimization is used in the short paths by the robot. Then the grids are prioritized and according to the grids priority in the short path, an integrated algorithm is proposed. By applying the proposed algorithm, the mobile robot move to the target along the optimal path without obstacle collision and deadlock. Finally, some experiments are provided to demonstrate the effectiveness of our proposed algorithm.