{"title":"群智能优化算法及其在移动机器人路径规划中的应用","authors":"Xiu-juan Lei, Fei Wang, Ying Tan","doi":"10.4018/978-1-4666-9572-6.CH011","DOIUrl":null,"url":null,"abstract":"Mobile robot path planning is generally a kind of optimal problems, which is to find a best path of a track between a starting point to a goal point in the constraint conditions. Mobile robot path planning can be divided into two categories according to different environment planning awareness information: one is the global path planning and the other is the local path planning. We employed ACO, PSO, FA, FOA, FWA and ABC swarm intelligent optimization algorithms to optimize the global and local path planning of mobile robot, and gave the detailed implement steps and the comparing results to show the feasibility of using swarm intelligence optimization algorithms to solve the robot path planning problems.","PeriodicalId":50067,"journal":{"name":"Journal of Rapid Methods and Automation in Microbiology","volume":"39 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Swarm Intelligent Optimization Algorithms and Its Application in Mobile Robot Path Planning\",\"authors\":\"Xiu-juan Lei, Fei Wang, Ying Tan\",\"doi\":\"10.4018/978-1-4666-9572-6.CH011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile robot path planning is generally a kind of optimal problems, which is to find a best path of a track between a starting point to a goal point in the constraint conditions. Mobile robot path planning can be divided into two categories according to different environment planning awareness information: one is the global path planning and the other is the local path planning. We employed ACO, PSO, FA, FOA, FWA and ABC swarm intelligent optimization algorithms to optimize the global and local path planning of mobile robot, and gave the detailed implement steps and the comparing results to show the feasibility of using swarm intelligence optimization algorithms to solve the robot path planning problems.\",\"PeriodicalId\":50067,\"journal\":{\"name\":\"Journal of Rapid Methods and Automation in Microbiology\",\"volume\":\"39 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Rapid Methods and Automation in Microbiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/978-1-4666-9572-6.CH011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Rapid Methods and Automation in Microbiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-4666-9572-6.CH011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Swarm Intelligent Optimization Algorithms and Its Application in Mobile Robot Path Planning
Mobile robot path planning is generally a kind of optimal problems, which is to find a best path of a track between a starting point to a goal point in the constraint conditions. Mobile robot path planning can be divided into two categories according to different environment planning awareness information: one is the global path planning and the other is the local path planning. We employed ACO, PSO, FA, FOA, FWA and ABC swarm intelligent optimization algorithms to optimize the global and local path planning of mobile robot, and gave the detailed implement steps and the comparing results to show the feasibility of using swarm intelligence optimization algorithms to solve the robot path planning problems.
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