Multi-target path planning for mobile robot based on improved PSO algorithm

An improved particle swarm optimization algorithm and the objective function of path planning are presented in this paper. First, the inverse learning strategy is used to initialize the particle swarm. At the same time, the inertia weight and learning factor are dynamically adjusted according to the iteration process of the algorithm, and the global search ability of the optimization algorithm is improved. At the same time, the convergence accuracy and stability of the algorithm are improved. In this paper, the selection of target points for mobile robots is transformed into solving TSP problem, and the improved particle swarm optimization algorithm is used to solve TSP problem and the optimization of path planning objective function. The experimental results show that the improved algorithm has better optimization ability, better security and smoothness of the robot trajectory, and improves the efficiency of multi-objective point path planning of the robot.