Path Planning of Mobile Robot Based on an Improved Genetic Algorithm
Aimed for the problems in traditional genetic algorithm of low search efficiency and easily falling into the local optimal solution,an improved genetic algorithm is proposed in this paper.So as to save the storage space,the simple one-dimensional code method is adopted to replace the method of complex two-dimensional coding.In the design of genetic operators,many operations such as crossover and mutation are redefined to avoid getting into the local optimum.Then the two fitness functions of collision-free path and the shortest distance are fused into one for the following genetic optimization.In the case of the same population parameters,100 trials are respectively developed with the method of improved genetic algorithm and traditional genetic algorithm.Among them,the improved genetic algorithm to search the optimal path gets to 95 times,and the shortest path is 20.9706.Besides,the average searching time takes up 217ms.While the number of traditional method to search for the optimal path reaches up to 62 times,the shortest path can be 25.0711,and the average searching time needs 345ms.So compared to the tests results referred above,the improved genetic algorithm is more efficient and can get a better solution than the traditional genetic algorithm.
genetic algorithm mobile robot path planning crossover operator mutation operator
Zhang Yi Dai En-can Ren Tong-hui
National Engineering Research and Development Center for Information Accessibility, Chongqing University of Posts and Telecommunication, Chongqing 400065, China
国际会议
重庆
英文
398-404
2016-03-21（万方平台首次上网日期，不代表论文的发表时间）