Path Planning of Coal Mine Rescue Robot Based on Particle Swarm Optimization Algorithm
In view of the existing problem of low search efficiency and easy occure scratching of coal mine rescue robots during search and rescue in downhole roadways,choosing coal mine rescue robots as the research object,a path planning solution scheme based on intelligent biomimetic algorithm is proposed.Through simulation experiments,downhole path planning research is carried out to analyze the problems faced by path planning algorithm in downhole applications;Describe the classification and usage scenarios of path planning algorithm,compare and analyze the advantages and disadvantages of the algorithm;Choose and adopt PSO particle swarm optimization algorithm,GWO grey wolf algorithm,and GA genetic algorithm,respectively,as the basic algorithms for path planning of coal mine rescue robots,and briefly analyze the algorithm principles;To verify the advantages and disadvantages of three algorithms for path planning,MATLAB simulation experiments are conducted to construct three different obstacle maps to simulate the driving routes of robots under complex paths.The results show that the PSO algorithm reduces the shortest path by 7.05%and 2.85%compared to the GWO algorithm and GA algorithm,respectively,the particle swarm optimization algorithm is higher in aspects of stability and path planning accuracy,meeting the needs of downhole rescue.
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