基于优化遗传算法的变电站巡检机器人路径规划方法研究OA

An in-depth study was conducted on the deficiencies and the causes of the existing genetic algorithms in path planning,and provides a detailed theoretical analysis.At the same time,the comparative study was conducted on the existing improved genetic algorithms,and the problems in their optimization process were summarized,such as slow convergence speed,easy trapping in local optima,and weak adaptive ability.The substation is taken as the research object,and the path of inspection robots from the starting point to the end point of the inspection is researched.The inspection scene is analyzed,the inspection scene model is established,and the inspection scheme is optimized.The improvement plan is proposed to solve problems such as path redundancy and the risk of local extrema.Matlab and ROS systems are used for modeling and testing to ensure the feasibility of the proposed solution.By establishing a scene model,the execution efficiency of the plan algorithm is analyzed,and the target points of the shortest and smoothest route in the plane is detected and designed.The simulation experiments of substation inspec-tion robot path planning based on optimized genetic algorithm is conducted across multi-complex scenarios.The experimental results demonstrate that this method can rapidly and effectively resolve the shortest path,and has stronger practicality and stability.