现代电子技术2026，Vol.49Issue(18)：168-173,6.DOI:10.16652/j.issn.1004-373X.2026.18.026
基于改进蚁群算法的路径重规划避障策略研究
Research on obstacle avoidance strategy for path replanning based on improved ant colony algorithm
摘要
Abstract
With the widespread application of mobile robots in industrial automation,logistics transportation,and other dynamic complex environments,path planning technology faces critical challenges such as frequent changes of dynamic obstacles,coexistence of static and dynamic obstacles,and insufficient real-time path planning performance.The collaborative static-dynamic obstacle detection and incremental path replanning strategy can achieve real-time obstacle prediction,dynamic path replanning,and stable robot operation.Specifically,the vector projection method enables rapid static obstacle identification,while a time-window-based approach predicts the trajectories of moving obstacles,allowing real-time updates to the temporary environmental model and local path adjustments.By integrating an improved ant colony algorithm,the strategy achieves efficient obstacle avoidance in hybrid environments while reducing the computational overhead of global replanning.The simulation experiments verify the effectiveness of the obstacle avoidance algorithm and strategy in complex dynamic scenarios.The collaborative detection and replanning strategy can effectively handle sudden obstacles,and complex multi-obstacle scenarios,successfully achieving autonomous obstacle avoidance.In typical situations such as head-on encounters,node conflicts,and same-direction chases,the algorithm can ensure both operational safety and pathfinding efficiency by the multi-stage path re-planning.关键词
避障策略/改进蚁群算法/路径重规划/动静态协同检测/向量投影法/搜索效率Key words
improved ant colony algorithm/path safety/search efficiency/obstacle avoidance strategy/collaborative static and dynamic obstacle detection/incremental path re-planning分类
信息技术与安全科学引用本文复制引用
高九州,郭彦博,王湘源,岳俊华..基于改进蚁群算法的路径重规划避障策略研究[J].现代电子技术,2026,49(18):168-173,6.基金项目
吉林省自然科学基金项目(YDZJ202201ZYTS561) （YDZJ202201ZYTS561）
吉林省教育厅科学研究项目(JJKH20250988KJ) （JJKH20250988KJ）
