电子科技2025，Vol.38Issue(1)：23-28,44,7.DOI:10.16180/j.cnki.issn1007-7820.2025.01.004
基于蚁群算法的智能路径规划
Intelligent Path Planning Based on Ant Colony Algorithm
摘要
Abstract
In view of the problem that it is difficult to reasonably plan the path after the mobile robot completes its self-positioning and map construction,which leads to the disordered movement of the mobile robot and the waste of resources,ant colony algorithm is adopted to realize the path planning of mobile robot in this study.Ant colony al-gorithm is a probabilistic algorithm to solve the optimal path in a problem.However,in the general ant colony algo-rithm,all parameters of the ant colony algorithm are unchanged,resulting in the result of the ant colony algorithm de-pendent on the pheromone parameters set in the algorithm.In order to solve the above problems,the parameters of ant colony algorithm and pheromone allocation are improved,and the pheromone update standard is improved by changing the pheromone volatility coefficient and pheromone update standard in each iteration and combining with heuristic factors.Setting the adjustable pheromone volatile factor increases the adaptability of the algorithm.Accord-ing to the meaningful parameter space,the path planning results of the traditional ant colony algorithm and the im-proved ant colony algorithm are compared under different environments.The path length of the improved ant colony algorithm is reduced by 4.48%and 8.54%,respectively,and no path crossover nodes are generated,which a-chieves the expected effect of reasonable path planning for mobile robots.关键词
移动机器人/蚁群算法/路径规划/概率型算法/最佳路径/信息素挥发系数/信息素更新标准/参数空间Key words
mobile robot/ant colony algorithm/path planning/probabilistic algorithm/optimal path/phero-mone volatilization coefficient/pheromone renewal standard/parameter space分类
信息技术与安全科学引用本文复制引用
佟云昊,席志红..基于蚁群算法的智能路径规划[J].电子科技,2025,38(1):23-28,44,7.基金项目
国家自然科学基金(62001136)National Natural Science Foundation of China(62001136) （62001136）
