[1]李江涛,董长浩.巡检机器人移动路径自适应规划研究[J].工业仪表与自动化装置,2026,(01):57-62.[doi:10.19950/j.cnki.CN61-1121/TH.2026.01.011]
　LI Jiangtao,DONG Changhao.Research on adaptive path planning for inspection robots[J].Industrial Instrumentation & Automation,2026,(01):57-62.[doi:10.19950/j.cnki.CN61-1121/TH.2026.01.011]
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巡检机器人移动路径自适应规划研究(/HTML)

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2026年01期
页码:
57-62
栏目:
出版日期:
2026-02-15

文章信息/Info

Title:
Research on adaptive path planning for inspection robots
文章编号:
1000-0682（2026）01-0057-06
作者:
李江涛1; 董长浩2
1.国能神东煤炭集团洗选中心，陕西 榆林 719315；2.西安理工大学,陕西 西安 710061
Author(s):
LI Jiangtao1;  DONG Changhao2
1.Guoneng Shendong Coal Group Washing Center, Shaanxi Yulin 719315, China;2.Xi’an University of Technology, Shaanxi Xi’an 710061, China
关键词:
巡检机器人; 自适应雪雁算法; 路径规划; 余弦自适应策略
Keywords:
inspection robot;  adaptive snow geese algorithm;  path planning;  cosine adaptive strategy
分类号:
TP273
DOI:
10.19950/j.cnki.CN61-1121/TH.2026.01.011
文献标志码:
A
摘要:
为解决巡检机器人在复杂作业环境中路径规划效率低、精度不足等问题，提出了基于增强型雪雁算法(ESGA)。建立了巡检机器人路径规划模型；在雪雁算法的基础上，引入3种优化策略对算法进行改进，采用自适应切换策略实现探索与开发的动态平衡，引入主导群体引导策略加速收敛并提升搜索方向的稳定性，设计主导随机差分搜索策略增强局部开发能力以避免陷入局部最优；通过3个基准测试函数对比验证ESGA与SGA的性能差异；构建了巡检机器人测试实验，将ESGA与雪雁算法(SGA)、粒子群优化(PSO)、遗传算法(GA)及灰狼优化算法(GWO)等进行路径规划效果对比。实验结果表明，ESGA算法在复杂环境下能够规划出更短的移动路径，同时具备更高的计算效率与稳定性。
Abstract:
To address issues such as low path planning efficiency and insufficient accuracy of inspection robots in complex operating environments, an enhanced snow geese algorithm (ESGA) is proposed. A path planning model for inspection robots is established. Based on the snow geese algorithm (SGA), three optimization strategies are introduced to improve the algorithm, an adaptive switching strategy is adopted to achieve dynamic balance between exploration and exploitation; a dominant group guidance strategy is introduced to accelerate convergence and enhance the stability of search direction; a dominant stochastic differential search strategy is designed to strengthen local exploitation capability and avoid falling into local optima. The performance differences between ESGA and SGA are verified by comparison using three benchmark test functions. A test experiment for inspection robots is constructed, and the path planning effects of ESGA are compared with those of SGA, particle swarm optimization (PSO), genetic algorithm (GA), grey wolf optimizer (GWO), and other algorithms. The experimental results show that the ESGA can plan shorter moving paths in complex environments, while possessing higher computational efficiency and stability.

参考文献/References:

[1] 孙宁,胡云雷,陈宇飞.基于改进A算法的轮式巡检机器人路径规划方法[J].湖南大学学报(自然科学版),2025,52(08):103-110.

[2] 张辉,苏国用,赵东洋,等.基于改进 A算法的矿用巡检机器人路径规划[J].太原理工大学学报,2025,56(03): 559-566.
[3] 张伟民,徐森生,张月.基于改进A算法的室内巡检机器人路径规划研究[J].机械工程学报,2024,60(20):315-326.
[4] 乔道迹,张艳兵.多障碍环境下巡检机器人路径规划优化研究[J].现代电子技术,2025,48(01):130-134.
[5] 郭彬,牛毅,李根,等.基于改进麻雀搜索算法的电气巡检机器人路径规划方法[J].办公自动化,2025,30(16):110-112.
[6] 徐雯清,顾大德,刘有志,等.基于自适应金豺狼优化算法的巡检机器人路径规划[J].核电子学与探测技术,2024,44 (05):955-962.
[7] 朱翠,罗宇豪,王占刚,等.新型蚁群算法规划核电厂巡检机器人路径[J].核电子学与探测技术,2025,45(01):107-115.
[8] 高金喆,寇志伟,许寒琪,等.基于改进鱼群算法的牧场巡检机器人路径规划研究[J].中国农机化学报,2024,45 (11):202-208.
[9] 张伏,韩伟东,鲍若飞,等.融合改进A*与DWA算法的车间移动机器人路径规划[J].吉林大学学报(工学版),2025,55(09):3020-3031.
[10] 完颜丹丹,孙士保,赵威.结合改进A*和改进DWA的电力巡检机器人路径规划方法[J].机械设计与制造,2025,(09):303-308.
[11] 邓军,李钊,王伟峰,等.基于改进 ILS-RVND 算法的工业园区智能巡检机器人路径规划方法[J/OL].现代电子技术, 2021,44(18):167-171.
[12] 许寒琪,寇志伟,李欣,等.基于EDDPG的农业巡检机器人路径规划研究[J/OL].中国农机化学报,1-8[2025-11-11].https://link.cnki.net/urlid/32.1837.s.20250730.1543.003.

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备注/Memo

备注/Memo:
收稿日期：2025-09-22基金项目：陕西省自然科学项目(2020LM-022)第一作者：李江涛（1980—），男，山西翼城人，大学本科，高级工程师，研究方向为复杂机电系统控制。E-mail: lijiangtao_2025@126.com
更新日期/Last Update: 1900-01-01