{"title":"基于连接算子的工业机械臂定位算法","authors":"M. Tomic, Branko Miloradovic, M. Jankovic","doi":"10.1109/NEUREL.2012.6419964","DOIUrl":null,"url":null,"abstract":"In this paper the solution of inverse kinematics problem and positioning of the industrial manipulator (ROBED03) with five degrees of freedom are presented. The algorithm is based on combination of Artificial Neural Networks (ANN) and Genetic Algorithm (GA).ANN was used for rough positioning providing the inputs for GA which performs precise adjustment. The algorithm was successfully tested in robot's working space.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Connectionist-genetic based algorithm for positioning industrial manipulator\",\"authors\":\"M. Tomic, Branko Miloradovic, M. Jankovic\",\"doi\":\"10.1109/NEUREL.2012.6419964\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper the solution of inverse kinematics problem and positioning of the industrial manipulator (ROBED03) with five degrees of freedom are presented. The algorithm is based on combination of Artificial Neural Networks (ANN) and Genetic Algorithm (GA).ANN was used for rough positioning providing the inputs for GA which performs precise adjustment. The algorithm was successfully tested in robot's working space.\",\"PeriodicalId\":343718,\"journal\":{\"name\":\"11th Symposium on Neural Network Applications in Electrical Engineering\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"11th Symposium on Neural Network Applications in Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NEUREL.2012.6419964\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"11th Symposium on Neural Network Applications in Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEUREL.2012.6419964","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Connectionist-genetic based algorithm for positioning industrial manipulator
In this paper the solution of inverse kinematics problem and positioning of the industrial manipulator (ROBED03) with five degrees of freedom are presented. The algorithm is based on combination of Artificial Neural Networks (ANN) and Genetic Algorithm (GA).ANN was used for rough positioning providing the inputs for GA which performs precise adjustment. The algorithm was successfully tested in robot's working space.
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