深圳大学学报（理工版）2025，Vol.42Issue(4)：447-454,8.DOI:10.3724/SP.J.1249.2025.04447
基于三种群粒子群优化策略的移动机器人路径规划
Mobile robot path planning based on a three-population particle swarm optimization strategy
摘要
Abstract
To address the issues of insufficient global search capability,proneness to falling into local optima,and poor path quality in mobile robot path planning in complex environments,this paper proposes a mobile robot path planning algorithm based on a three-population particle swarm optimization(TPPSO)strategy.The algorithm enhances global exploration and local exploitation capabilities through the collaborative evolution of three distinct populations:exploration,exploitation,and enhancement.The exploration population updates particle velocities by using a particle quality evaluation and random selection strategy;the exploitation population employs a dynamic adjustment mechanism for the linear cognition coefficient;and the enhancement population incorporates larger random components to mitigate the impact of local optima.To further increase swarm diversity,a random perturbation strategy is introduced when the algorithm's search performance stagnates.Benchmark function test results show that TPPSO outperforms the traditional PSO,SAVPSO,and RRT* algorithms in terms of both mean and standard deviation on unimodal functions(F1),unimodal functions with noise(F4),and multimodal functions(F9),conforming the algorithm's optimization performance and stability.In four 10 m×10 m two-dimensional standard environments,the generated paths effectively avoid obstacles and minimize unnecessary detours,achieving superior path quality.Experimental validation in complex scenarios shows a planning success rate of 91.5%in dynamic multi-obstacle environments,an average climb rate of 10.7%in three-dimensional environments,and a constraint satisfaction rate of 94.6%in multi-constraint environments.The experimental results indicate that the proposed algorithm can effectively solve the path planning problem for mobile robots in complex environments.关键词
计算机应用/路径规划/粒子群优化/进化算法/线性认知系数/随机扰动Key words
computer applications/path planning/particle swarm optimization/evolutionary algorithms/linear cogni-tion coefficient/random perturbation分类
信息技术与安全科学引用本文复制引用
王珂,姜春艳,黄黎,张新海..基于三种群粒子群优化策略的移动机器人路径规划[J].深圳大学学报（理工版）,2025,42(4):447-454,8.基金项目
National Natural Science Foundation of China(62106104) （62106104）
Teaching Reform Research Project of Jiangsu Open University(1017155JG2023/002) （1017155JG2023/002）
The"14th Five-Year"Special Scientific Research Planning of Jiangsu Open University(2023LYYB004) （2023LYYB004）
Jiangsu Province Quality Engineering Project(24 SJA-45) 国家自然科学基金资助项目(62106104) （24 SJA-45）
江苏开放大学教学改革研究课题资助项目(1017155JG2023/002) （1017155JG2023/002）
江苏开放大学"十四五"科研规划专项课题资助项目(2023LYYB004) （2023LYYB004）
江苏省精品工程课题资助项目(24SJA-45) （24SJA-45）
