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  • 标题:First-Order Synergies for Motion Planning of Anthropomorphic Dual-Arm Robots
  • 本地全文:下载
  • 作者:Néstor García ; Raúl Suárez ; Jan Rosell
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2017
  • 卷号:50
  • 期号:1
  • 页码:2247-2254
  • DOI:10.1016/j.ifacol.2017.08.187
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper addresses the problem of designing a planning algorithm for anthropomorphic dual-arm robotic systems to find paths that mimics the movements of real human beings by using first-order synergies (correlations between joint velocities). The key idea of the proposal is to convert captured human movements into a vector field of velocities, defined in the configuration space of the robot, and use it to guide the search of a solution path. The motion planning is solved using the proposed algorithm, called FOS-BKPIECE, that is a bidirectional version of the KPIECE planner working with an improved version of the extension procedure of the VF-RRT planner. The obtained robot movements follow the directions of the defined vector field and hence allow the robot to solve the task in a human-like fashion. The paper presents a description of the proposed approach as well as results from conceptual and application examples, the latter using a real anthropomorphic dual-arm robotic system. A thorough comparison with other previous planning algorithms shows that the proposed approach obtains better results.
  • 关键词:KeywordsRoboticsPath PlanningDual-Arm RobotsSynergiesHuman-Like Motions
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