{"title":"Cooperative manipulations based on genetic algorithms using contact information","authors":"T. Nagata, Kosuke Konishi, H. Zha","doi":"10.1109/IROS.1995.526248","DOIUrl":null,"url":null,"abstract":"This paper presents a new method for cooperative manipulations based on genetic algorithms using contact information. In order to apply genetic algorithms, each robot arm generates new information about object postures using its own contact information without using of any vision systems. The object postures are derived by calculating normal vectors of object surfaces. The system proposed on the basis of genetic algorithms determines forces which robot arms should apply to the objects by solving an optimization problem utilizing the generated and obtained information. Owing to genetic algorithms, the system has not only the adaptation to the change of the working environment, but also can determine the forces for robot arms without physical inconsistency.","PeriodicalId":124483,"journal":{"name":"Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.1995.526248","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
This paper presents a new method for cooperative manipulations based on genetic algorithms using contact information. In order to apply genetic algorithms, each robot arm generates new information about object postures using its own contact information without using of any vision systems. The object postures are derived by calculating normal vectors of object surfaces. The system proposed on the basis of genetic algorithms determines forces which robot arms should apply to the objects by solving an optimization problem utilizing the generated and obtained information. Owing to genetic algorithms, the system has not only the adaptation to the change of the working environment, but also can determine the forces for robot arms without physical inconsistency.