基于自适应遗传算法的光伏板清理机器人路径规划研究

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中图分类号：TH137.5 文献标志码：A 文章编号：1003-5168（2025）20-0048-04

DOI：10.19968/j.cnki.hnkj.1003-5168.2025.20.010

Research on Path Planning of Photovoltaic Panel Cleaning Robot Based onAdaptiveGeneticAlgorithm

TANG Bo WANG YuqinSHAO Jiale YANG LiyuWANG Weijun ZHANG Jiajun （School ofMechanicalEngineering，Chaohu University，Hefei 238O24，China）

Abstract： [Purposes] In response to the issues of path redundancy，long cleaning time，and high energy consumption of traditional photovoltaic panel cleaning robots in multi-region photovoltaic arrays，this paper proposes a path planning method based on an Adaptive Genetic Algorithm （AGA） to enhance the operational eficiency of robots and reduce energy consumption.[Methods]A dual-layer encoding mechanism is adopted，combined with the "adjacency-contamination" heuristic rule，to dynamically adjust the crossover and mutation probabilities of the genetic algorithm and optimize the cleaning path in real-time. Through a multi-objective fitness function，it comprehensively considers path length，cleaning time，and energy consumption to achieve coordinated optimization of the three.[Findings] Experiments show that in complex scenarios with 1OO stains，AGA shortens the path length by 20.24% ，reduces cleaning time by 21.99% ， and decreases energy consumption by 22.52% ，with synchronous optimization of the three indicators and similar magnitude.[Conclusions]AGA performs excellntly in terms of multiobjec

tive balance and scenario adaptability，effectively addressing the limitations of traditional methods and providing an effcient and energy-saving solution for the practical application of photovoltaic panel cleaning robots.

Keywords： photovoltaic panel; cleaning robot; AGA; multi-objective optimization; path planning

0 引言

随着光伏产业的迅猛发展，光伏板的清洁问题日益凸显。（剩余4173字）