{"title":"学习避免碰撞:移动机器人导航的强化学习范式","authors":"B.J.A. Kröse, J.W.M. van Dam","doi":"10.1016/S0066-4138(09)91052-7","DOIUrl":null,"url":null,"abstract":"<div><p>The paper describes a self-learning control system for a mobile robot. Based on sensor information the control system has to provide a steering signal in such a way that collisions are avoided. Since in our case no «examples« are available, the system learns on the basis of an external reinforcement signal which is negative in case of a collision and zero otherwise. We describe the adaptive algorithm which is used for a discrete coding of the state space, and the adaptive algorithm for learning the correct mapping from the input (state) vector to the output (steering) signal.</p></div>","PeriodicalId":100097,"journal":{"name":"Annual Review in Automatic Programming","volume":"17 ","pages":"Pages 317-321"},"PeriodicalIF":0.0000,"publicationDate":"1992-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0066-4138(09)91052-7","citationCount":"9","resultStr":"{\"title\":\"Learning to avoid collisions: A reinforcement learning paradigm for mobile robot navigation\",\"authors\":\"B.J.A. Kröse, J.W.M. van Dam\",\"doi\":\"10.1016/S0066-4138(09)91052-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The paper describes a self-learning control system for a mobile robot. Based on sensor information the control system has to provide a steering signal in such a way that collisions are avoided. Since in our case no «examples« are available, the system learns on the basis of an external reinforcement signal which is negative in case of a collision and zero otherwise. We describe the adaptive algorithm which is used for a discrete coding of the state space, and the adaptive algorithm for learning the correct mapping from the input (state) vector to the output (steering) signal.</p></div>\",\"PeriodicalId\":100097,\"journal\":{\"name\":\"Annual Review in Automatic Programming\",\"volume\":\"17 \",\"pages\":\"Pages 317-321\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S0066-4138(09)91052-7\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual Review in Automatic Programming\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0066413809910527\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review in Automatic Programming","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0066413809910527","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Learning to avoid collisions: A reinforcement learning paradigm for mobile robot navigation
The paper describes a self-learning control system for a mobile robot. Based on sensor information the control system has to provide a steering signal in such a way that collisions are avoided. Since in our case no «examples« are available, the system learns on the basis of an external reinforcement signal which is negative in case of a collision and zero otherwise. We describe the adaptive algorithm which is used for a discrete coding of the state space, and the adaptive algorithm for learning the correct mapping from the input (state) vector to the output (steering) signal.
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