{"title":"动态环境下移动机器人导航的分层路径规划方法","authors":"Zeng Bi, Yang Yimin, Yuan Wei","doi":"10.1109/INDIN.2008.4618127","DOIUrl":null,"url":null,"abstract":"In view of the environment uncertainty of mobile robot navigating under the unknown and dynamic environments, the paper adopts hierarchical path planning ways which is two layers of global and the local optimization have been combined to implement autonomous mobile robot navigating. The genetic algorithm and the fuzzy theory were applied in the two layers separately, the genetic annealing algorithm is used to global path planning, and the hierarchical fuzzy coordinated strategy is used to local optimization procedure. It results in fewer rules, as well as much simplified and flexible design where new behaviors can be added easily. The simulation experiments indicate the effectiveness of the proposed methods.","PeriodicalId":112553,"journal":{"name":"2008 6th IEEE International Conference on Industrial Informatics","volume":"91 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Hierarchical path planning approach for mobile robot navigation under the dynamic environment\",\"authors\":\"Zeng Bi, Yang Yimin, Yuan Wei\",\"doi\":\"10.1109/INDIN.2008.4618127\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In view of the environment uncertainty of mobile robot navigating under the unknown and dynamic environments, the paper adopts hierarchical path planning ways which is two layers of global and the local optimization have been combined to implement autonomous mobile robot navigating. The genetic algorithm and the fuzzy theory were applied in the two layers separately, the genetic annealing algorithm is used to global path planning, and the hierarchical fuzzy coordinated strategy is used to local optimization procedure. It results in fewer rules, as well as much simplified and flexible design where new behaviors can be added easily. The simulation experiments indicate the effectiveness of the proposed methods.\",\"PeriodicalId\":112553,\"journal\":{\"name\":\"2008 6th IEEE International Conference on Industrial Informatics\",\"volume\":\"91 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 6th IEEE International Conference on Industrial Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INDIN.2008.4618127\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 6th IEEE International Conference on Industrial Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN.2008.4618127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hierarchical path planning approach for mobile robot navigation under the dynamic environment
In view of the environment uncertainty of mobile robot navigating under the unknown and dynamic environments, the paper adopts hierarchical path planning ways which is two layers of global and the local optimization have been combined to implement autonomous mobile robot navigating. The genetic algorithm and the fuzzy theory were applied in the two layers separately, the genetic annealing algorithm is used to global path planning, and the hierarchical fuzzy coordinated strategy is used to local optimization procedure. It results in fewer rules, as well as much simplified and flexible design where new behaviors can be added easily. The simulation experiments indicate the effectiveness of the proposed methods.