Path planning based on improved multi-objective particle swarm algorithm
YiQin Duan, Yi Zhang, Bin Zhang, Yusen Wang · 2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC) · 2020
This paper proposes an improved multi-objective particle swarm algorithm (MOPSO) to solve the path planning problem of mobile robots. The path planning problem is reduced to the three-objective optimization problem of constraint of path length, path smoothness, and path safety. In this paper, a multiobjective particle swarm optimization algorithm is used, so that multiple targets for path planning can be optimized simultaneously and reasonably, and a single run can provide multiple optimized candidate paths. Aiming at the common problems of multi-objective optimization algorithms, multiple fusion strategies were proposed to improve the effectiveness of the algorithm. Finally, simulation results verify the ability of the improved algorithm to generate high-quality Pareto optimal paths.