{"title":"基于遗传算法的协作机器人最优路径规划与力矩最小化","authors":"D. Garg, Manish Kumar","doi":"10.1115/imece2001/dsc-24509","DOIUrl":null,"url":null,"abstract":"\n This paper presents the formulation and application of a genetic algorithm based strategy for the determination of an optimal trajectory for a multiple robotic configuration. First, the motivation for multiple robot control and the current state-of-art in the field of cooperating robots are briefly given. This is followed by a discussion of energy minimization techniques in the context of robotics, and finally, the principles of using genetic algorithms as an optimization tool are included. The initial and final position of the end effector are specified. Two cases, one of a single manipulator, and the other of two cooperating manipulators carrying a common payload illustrate the approach proposed. The genetic algorithm identifies the optimal trajectory based on minimum joint torque requirements. The minimization of a suitably defined performance index involving joint torques implies that the trajectory thus obtained requires the least amount of torque.","PeriodicalId":90691,"journal":{"name":"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","volume":"49 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Optimal Path Planning and Torque Minimization via Genetic Algorithm Applied to Cooperating Robotic Manipulators\",\"authors\":\"D. Garg, Manish Kumar\",\"doi\":\"10.1115/imece2001/dsc-24509\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n This paper presents the formulation and application of a genetic algorithm based strategy for the determination of an optimal trajectory for a multiple robotic configuration. First, the motivation for multiple robot control and the current state-of-art in the field of cooperating robots are briefly given. This is followed by a discussion of energy minimization techniques in the context of robotics, and finally, the principles of using genetic algorithms as an optimization tool are included. The initial and final position of the end effector are specified. Two cases, one of a single manipulator, and the other of two cooperating manipulators carrying a common payload illustrate the approach proposed. The genetic algorithm identifies the optimal trajectory based on minimum joint torque requirements. The minimization of a suitably defined performance index involving joint torques implies that the trajectory thus obtained requires the least amount of torque.\",\"PeriodicalId\":90691,\"journal\":{\"name\":\"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference\",\"volume\":\"49 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/imece2001/dsc-24509\",\"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 the ASME Dynamic Systems and Control Conference. ASME Dynamic Systems and Control Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/imece2001/dsc-24509","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Path Planning and Torque Minimization via Genetic Algorithm Applied to Cooperating Robotic Manipulators
This paper presents the formulation and application of a genetic algorithm based strategy for the determination of an optimal trajectory for a multiple robotic configuration. First, the motivation for multiple robot control and the current state-of-art in the field of cooperating robots are briefly given. This is followed by a discussion of energy minimization techniques in the context of robotics, and finally, the principles of using genetic algorithms as an optimization tool are included. The initial and final position of the end effector are specified. Two cases, one of a single manipulator, and the other of two cooperating manipulators carrying a common payload illustrate the approach proposed. The genetic algorithm identifies the optimal trajectory based on minimum joint torque requirements. The minimization of a suitably defined performance index involving joint torques implies that the trajectory thus obtained requires the least amount of torque.