重庆理工大学学报2025，Vol.39Issue(5)：133-140,8.DOI:10.3969/j.issn.1674-8425(z).2025.03.017
多策略改进蜣螂优化算法移动机器人路径规划
Multi-strategy improved dung beetle optimization algorithm for mobile robot path planning
摘要
Abstract
To address the problems of path length and local optimization in path planning of traditional dung beetle optimization algorithm,we propose an improved dung beetle optimization algorithm.First,Logistics is used to initialize the initial population chaotically,so that the dung beetle population is more evenly distributed in the search space to improve the quality of the population.Then,a somersault strategy is introduced in the foraging dung beetle position updating stage to expand the search range of the algorithm and improve the algorithm's global search ability.Finally,an adaptive factor-based stealing position updating strategy is introduced in the stealing dung beetle position updating stage to reduce the probability of the algorithm falling into local optimum and balance the global and local search ability of the algorithm.Three different raster maps are built as the working environment model of the robot using MATLAB,and the improved dung beetle optimization algorithm and four traditional algorithms are simulated and compared in the two kinds of maps.Our results show our improved dung beetle optimization algorithm markedly reduces the average path length,the average number of iterations and the standard deviation of path length,demonstrating it delivers superior performances in path planning.关键词
蜣螂算法/移动机器人/路径规划/翻筋斗觅食策略Key words
dung beetle algorithm/mobile robot/route planning/somersault foraging分类
信息技术与安全科学引用本文复制引用
贾志绚,谢卓晨,葛丽娜..多策略改进蜣螂优化算法移动机器人路径规划[J].重庆理工大学学报,2025,39(5):133-140,8.基金项目
山西省科技战略研究专项计划项目(202304031401079) （202304031401079）
