{"title":"服务机器人路径规划","authors":"Ruining Li","doi":"10.1109/WCMEIM56910.2022.10021507","DOIUrl":null,"url":null,"abstract":"Path Planning is an essential aspect of the navigation of mobile service robots. The problem of path planning includes low time efficiency, large memory cost, local optimum, and slow speed in finding the global optimum. This paper reviews three main path planning algorithms and their extensions for the service robots. The first one is Ant Colony Optimization (ACO). The second algorithm is Particle Swarm Optimization (PSO) and some hybrid PSO-related algorithms. The third one is a conventional algorithm named Rapidly Exploring Random Tree (RRT).","PeriodicalId":202270,"journal":{"name":"2022 5th World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Path Planning for Service Robots\",\"authors\":\"Ruining Li\",\"doi\":\"10.1109/WCMEIM56910.2022.10021507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Path Planning is an essential aspect of the navigation of mobile service robots. The problem of path planning includes low time efficiency, large memory cost, local optimum, and slow speed in finding the global optimum. This paper reviews three main path planning algorithms and their extensions for the service robots. The first one is Ant Colony Optimization (ACO). The second algorithm is Particle Swarm Optimization (PSO) and some hybrid PSO-related algorithms. The third one is a conventional algorithm named Rapidly Exploring Random Tree (RRT).\",\"PeriodicalId\":202270,\"journal\":{\"name\":\"2022 5th World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM)\",\"volume\":\"101 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 5th World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCMEIM56910.2022.10021507\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCMEIM56910.2022.10021507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Path Planning is an essential aspect of the navigation of mobile service robots. The problem of path planning includes low time efficiency, large memory cost, local optimum, and slow speed in finding the global optimum. This paper reviews three main path planning algorithms and their extensions for the service robots. The first one is Ant Colony Optimization (ACO). The second algorithm is Particle Swarm Optimization (PSO) and some hybrid PSO-related algorithms. The third one is a conventional algorithm named Rapidly Exploring Random Tree (RRT).
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