{"title":"基于连接分配和地形编码的机器人逆运动学快速学习","authors":"J. Hakala, G. Fahner, R. Eckmiller","doi":"10.1109/IJCNN.1991.170618","DOIUrl":null,"url":null,"abstract":"An adaptive neural structure for robot control based on homogeneous encoding in a topographical manner is developed. An intermediate representation (IRep) is adaptively generated using a novel learning scheme, CATE. The connection assignment rules of CATE keep the number of IRep-neurons as small as possible, while maintaining the desired mapping accuracy. This adaptive net (CATEnet) was successfully applied to embed the inverse kinematics of a redundant, planar robot arm (four-joint-machine) with only a few presentations of the learning set. The mapping solution incorporated local optimization of a cost function to account for a limited joint range and to avoid singularities.<<ETX>>","PeriodicalId":211135,"journal":{"name":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1991-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Rapid learning of inverse robot kinematics based on connection assignment and topographical encoding (CATE)\",\"authors\":\"J. Hakala, G. Fahner, R. Eckmiller\",\"doi\":\"10.1109/IJCNN.1991.170618\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An adaptive neural structure for robot control based on homogeneous encoding in a topographical manner is developed. An intermediate representation (IRep) is adaptively generated using a novel learning scheme, CATE. The connection assignment rules of CATE keep the number of IRep-neurons as small as possible, while maintaining the desired mapping accuracy. This adaptive net (CATEnet) was successfully applied to embed the inverse kinematics of a redundant, planar robot arm (four-joint-machine) with only a few presentations of the learning set. The mapping solution incorporated local optimization of a cost function to account for a limited joint range and to avoid singularities.<<ETX>>\",\"PeriodicalId\":211135,\"journal\":{\"name\":\"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.1991.170618\",\"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] 1991 IEEE International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1991.170618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Rapid learning of inverse robot kinematics based on connection assignment and topographical encoding (CATE)
An adaptive neural structure for robot control based on homogeneous encoding in a topographical manner is developed. An intermediate representation (IRep) is adaptively generated using a novel learning scheme, CATE. The connection assignment rules of CATE keep the number of IRep-neurons as small as possible, while maintaining the desired mapping accuracy. This adaptive net (CATEnet) was successfully applied to embed the inverse kinematics of a redundant, planar robot arm (four-joint-machine) with only a few presentations of the learning set. The mapping solution incorporated local optimization of a cost function to account for a limited joint range and to avoid singularities.<>