A method for solving local minimum problem of local path planning based on particle swarm optimization

Abstract

In this paper, a local path planning algorithm based on particle swarm optimization is adopted. The obstacle avoidance principle of this method is to build a virtual robot on the edge of the obstacle and allowing it to move along the edge of the obstacle. The information of the virtual robot can be given based on the message of the actual mobile robot. The corresponding cost function can be designed. Then, the cost function is solved by particle swarm optimization algorithm. The calculated optimal value is the control input at the next moment. However, this method has its limitations. When the mobile robot encounters an obstacle like a corner, it will fall into the local minimum. Therefore, we propose a virtual target point method to solve the local minimum problem. At last, simulation experiments show that the method can effectively avoid obstacles and get away from the local minimum point to reach the target position.