{"title":"基于遗传算法的移动机器人路径规划","authors":"A. Ghorbani, S. Shiry, A. Nodehi","doi":"10.1109/ICFCC.2009.28","DOIUrl":null,"url":null,"abstract":"Mobile robot global path planning in a static environment is an important problem. This paper proposes a method of global path planning based on genetic algorithm to reach an optimum path for mobile robot with obstacle avoidance. In this method for decreasing the complexity, the two-dimensional coding for the path via-points was converted to one-dimensional coding and the fitness of both of the collision avoidance path and the shortest distance are integrated into a fitness function. The simulation results shows that the proposed method is accurate and effective.","PeriodicalId":338489,"journal":{"name":"2009 International Conference on Future Computer and Communication","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"46","resultStr":"{\"title\":\"Using Genetic Algorithm for a Mobile Robot Path Planning\",\"authors\":\"A. Ghorbani, S. Shiry, A. Nodehi\",\"doi\":\"10.1109/ICFCC.2009.28\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile robot global path planning in a static environment is an important problem. This paper proposes a method of global path planning based on genetic algorithm to reach an optimum path for mobile robot with obstacle avoidance. In this method for decreasing the complexity, the two-dimensional coding for the path via-points was converted to one-dimensional coding and the fitness of both of the collision avoidance path and the shortest distance are integrated into a fitness function. The simulation results shows that the proposed method is accurate and effective.\",\"PeriodicalId\":338489,\"journal\":{\"name\":\"2009 International Conference on Future Computer and Communication\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"46\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Future Computer and Communication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICFCC.2009.28\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Future Computer and Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFCC.2009.28","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Genetic Algorithm for a Mobile Robot Path Planning
Mobile robot global path planning in a static environment is an important problem. This paper proposes a method of global path planning based on genetic algorithm to reach an optimum path for mobile robot with obstacle avoidance. In this method for decreasing the complexity, the two-dimensional coding for the path via-points was converted to one-dimensional coding and the fitness of both of the collision avoidance path and the shortest distance are integrated into a fitness function. The simulation results shows that the proposed method is accurate and effective.
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