文献类型：期刊文献

英文题名：Research on Path Planning for Mobile Robot Using the Enhanced Artificial Lemming Algorithm

作者：Qu, Pengju Song, Xiaohui Zhou, Zhijin

通信作者：Qu, PJ[1]

机构：[1]Guizhou Inst Technol, Engn Training Ctr, Guiyang 550025, Peoples R China;[2]Anshun Univ, Coll Agr, Anshun 561000, Peoples R China

第一机构：贵州理工学院

通信机构：corresponding author), Guizhou Inst Technol, Engn Training Ctr, Guiyang 550025, Peoples R China.|贵州理工学院;

年份：2025

卷号：13

期号：21

外文期刊名：MATHEMATICS

收录：;Scopus(收录号：2-s2.0-105021506473);WOS:【SCI-EXPANDED(收录号:WOS:001612774600001)】；

基金：This research was funded by the National Natural Science Foundation of China (No. 52065010 and No. 52165063). The Key Laboratory of New Power System Operation Control of Guizhou Province (Qiankehe Platform ZSYS[2025]007).

语种：英文

外文关键词：mobile robot; planning issues; algorithm; meta-heuristic

摘要：To address the key challenges in shortest path planning for known static obstacle maps-such as the tendency to converge to local optima in U-shaped/narrow obstacle regions, unbalanced computational efficiency, and suboptimal path quality-this paper presents an enhanced Artificial Lemming Algorithm (DMSALAs). The algorithm integrates a dynamic adaptive mechanism, a hybrid Nelder-Mead method, and a localized perturbation strategy to improve the search performance of ALAs. To validate DMSALAs efficacy, we conducted ablation studies and performance comparisons on the IEEE CEC 2017 and CEC 2022 benchmark suites. Furthermore, we evaluated the algorithm in mobile robot path planning scenarios, including simulated grid maps (10 x 10, 20 x 20, 30 x 30, 40 x 40) and a real-world experimental environment built by our team. These experiments confirm that DMSALAs effectively balance optimization accuracy and practical applicability in path planning problems.