华南农业大学学报2017，Vol.38Issue(5)：110-116,7.DOI:10.7671/j.issn.1001-411X.2017.05.019
基于分组和精英策略的遗传算法在机器人导航上的应用
Application of genetic algorithm based on group and elite strategy for robot navigation
摘要
Abstract
[Objective] To solve the problems that picking robot could not find the multipath quickly and accurately in planning route in complex plantation environment,a genetic algorithm based on group and elite strategy (GGABE) was proposed.[Method] Firstly,an initial population was generated and was divided into several groups using the Sigmoid function.After n times of operations of selections,crossovers and mutations in each group separately,k optimal paths with equal length were then acquired in each group.Comparing the optimal paths among different groups,the shortest paths were chosen as the final optimal paths.With all population parameters being the same,three types of algorithms,including simple genetic algorithm(SGA),ungrouped elite genetic algorithm (EGA) and GGABE,were tested 50 times respectively on 15 × 15 and 25 ×25 maps.The prototype verification experiments were carried out in the plantation.[Result] Eight shortest paths with the average length of 20.970 6 were found in map 1 by GGABE.Only one shortest path was found in map 1 with the other two algorithms.Eight shortest paths with the average length of 38.041 6 were found in map 2 by GGABE.Three optimal paths were found in each of the 50 verification experiments,and the average consumption time for route planning was 15.543 319 s.[Conclusion] GGABE has fast convergence speed and can quickly and accurately find out all optimal paths,which are able to traverse the entire plantation,from the map.关键词
分组/精英策略/采摘机器人/遗传算法/优势个体/路径规划/导航Key words
group/elite strategy/picking robot/genetic algorithm/advantageous individual/route planning/navigation分类
信息技术与安全科学引用本文复制引用
谢忠红,王培,顾宝兴,姬长英,田光兆..基于分组和精英策略的遗传算法在机器人导航上的应用[J].华南农业大学学报,2017,38(5):110-116,7.基金项目
国家自然科学基金(31401291) （31401291）
江苏省自然科学基金(BK20140720) （BK20140720）
中央高校基本业务费(KYZ201670) （KYZ201670）
