{"title":"基于模糊决策方法的移动机器人导航行为控制","authors":"H. Beom, K. Koh, H. Cho","doi":"10.1109/IROS.1994.407597","DOIUrl":null,"url":null,"abstract":"This paper proposes a sensor-based navigation which utilizes multicriteria decision making method in uncertain environments. The multicriteria decision-maker using fuzzy sets is used to select one of avoidance and goal-seeking behaviors according to global mission from higher level planner and situation around the mobile robot. Two behaviors are designed to produce the prescribed responses to currently perceived sensory information using fuzzy logic and reinforcement learning. A decision function to appropriately select one of two behaviors is formulated by use of a fuzzy set. The optimal alternative of two behaviors is defined as that achieving the highest degree of membership in fuzzy decision function. The effectiveness of the proposed method is verified by a series of simulations.<<ETX>>","PeriodicalId":437805,"journal":{"name":"Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Behavioral control in mobile robot navigation using fuzzy decision making approach\",\"authors\":\"H. Beom, K. Koh, H. Cho\",\"doi\":\"10.1109/IROS.1994.407597\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a sensor-based navigation which utilizes multicriteria decision making method in uncertain environments. The multicriteria decision-maker using fuzzy sets is used to select one of avoidance and goal-seeking behaviors according to global mission from higher level planner and situation around the mobile robot. Two behaviors are designed to produce the prescribed responses to currently perceived sensory information using fuzzy logic and reinforcement learning. A decision function to appropriately select one of two behaviors is formulated by use of a fuzzy set. The optimal alternative of two behaviors is defined as that achieving the highest degree of membership in fuzzy decision function. The effectiveness of the proposed method is verified by a series of simulations.<<ETX>>\",\"PeriodicalId\":437805,\"journal\":{\"name\":\"Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IROS.1994.407597\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.1994.407597","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Behavioral control in mobile robot navigation using fuzzy decision making approach
This paper proposes a sensor-based navigation which utilizes multicriteria decision making method in uncertain environments. The multicriteria decision-maker using fuzzy sets is used to select one of avoidance and goal-seeking behaviors according to global mission from higher level planner and situation around the mobile robot. Two behaviors are designed to produce the prescribed responses to currently perceived sensory information using fuzzy logic and reinforcement learning. A decision function to appropriately select one of two behaviors is formulated by use of a fuzzy set. The optimal alternative of two behaviors is defined as that achieving the highest degree of membership in fuzzy decision function. The effectiveness of the proposed method is verified by a series of simulations.<>