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《Journal of Beijing Union University》 2018-01
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AGV Path Planning Based on Improved Genetic Algorithm

Yuan Guangming;Zhai Yunfei;Ding Chengjun;Zhang Peng;Institute of Mechanical Engineering,Hebei University of Technology;  
In order to solve the problem that the path planning algorithm in AGV automation production line has the number of turns,which is not conducive to the automatic control of AGV,an improved genetic algorithm is proposed. In order to improve the efficiency of AGV automatic control,the algorithm introduces the turning factor. Aiming at the problem of slow convergence of the path planning in the traditional genetic algorithm,the traditional elitism strategy is improved with hierarchical method. In the process of evolutionary algorithm,the crossover probability and mutation probability are dynamically adjusted according to the change of individual fitness,and the convergence speed of the algorithm is accelerated. Matlab simulation results show that the improved genetic algorithm can plan a more reasonable path,and the number of turns is reduced compared with the traditional methods,and the quality of the search path has been improved,which show that the algorithm can meet the requirements of automated production line AGV path planning.
【Fund】: 天津市科技支撑计划项目(14ZCDZGX00811);天津市科技支撑计划项目(13ZCZDGX01200);; 天津市产学研合作项目(14ZCZDSF00025)
【CateGory Index】: TP18;TP23
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