Research on Human-Robot Collaboration Method for Parallel Robots Oriented to Segment Docking

被引:2
|
作者
Sun, Deyuan [1 ,2 ]
Wang, Junyi [2 ,3 ,4 ]
Xu, Zhigang [2 ,3 ,4 ]
Bao, Jianwen [2 ]
Lu, Han [2 ,4 ,5 ]
机构
[1] Shenyang Univ Technol, Sch Mech Engn, Shenyang 110870, Peoples R China
[2] Chinese Acad Sci, Shenyang Inst Automat, Shenyang 110016, Peoples R China
[3] Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Shenyang 110016, Peoples R China
[4] Chinese Acad Sci, Inst Robot & Intelligent Mfg, Shenyang 110169, Peoples R China
[5] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
关键词
parallel robot; admittance control; fractional-order control; robust control; human-robot collaboration; CONTROL SCHEME;
D O I
10.3390/s24061747
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In the field of aerospace, large and heavy cabin segments present a significant challenge in assembling space engines. The substantial inertial force of cabin segments' mass often leads to unexpected motion during docking, resulting in segment collisions, making it challenging to ensure the accuracy and quality of engine segment docking. While traditional manual docking leverages workers' expertise, the intensity of the labor and low productivity are impractical for real-world applications. Human-robot collaboration can effectively integrate the advantages of humans and robots. Parallel robots, known for their high precision and load-bearing capacity, are extensively used in precision assembly under heavy load conditions. Therefore, human-parallel-robot collaboration is an excellent solution for such problems. In this paper, a framework is proposed that is easy to realize in production, using human-parallel-robot collaboration technology for cabin segment docking. A fractional-order variable damping admittance control and an inverse dynamics robust controller are proposed to enhance the robot's compliance, responsiveness, and trajectory tracking accuracy during collaborative assembly. This allows operators to dynamically adjust the robot's motion in real-time, counterbalancing inertial forces and preventing collisions between segments. Segment docking assembly experiments are performed using the Stewart platform in this study. The results show that the proposed method allows the robot to swiftly respond to interaction forces, maintaining compliance and stable motion accuracy even under unknown interaction forces.
引用
收藏
页数:17
相关论文
共 50 条
  • [41] Evaluating Fluency in Human-Robot Collaboration
    Hoffman, Guy
    IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 2019, 49 (03) : 209 - 218
  • [42] Human-Robot Collaboration for a Shared Mission
    Karami, Abir-Beatrice
    Jeanpierre, Laurent
    Mouaddib, Abdel-Illah
    PROCEEDINGS OF THE 5TH ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION (HRI 2010), 2010, : 155 - 156
  • [43] Qualification requirements for human-robot collaboration
    Weber M.-A.
    Schüth N.J.
    Stowasser S.
    ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb, 2018, 113 (10): : 619 - 622
  • [44] Human motion prediction for human-robot collaboration
    Liu, Hongyi
    Wang, Lihui
    JOURNAL OF MANUFACTURING SYSTEMS, 2017, 44 : 287 - 294
  • [45] DETERMINATION OF THE WORKSPACE OF A 3-PRPR PARALLEL MECHANISM FOR HUMAN-ROBOT COLLABORATION
    Lecours, Alexandre
    Gosselin, Clement
    TRANSACTIONS OF THE CANADIAN SOCIETY FOR MECHANICAL ENGINEERING, 2009, 33 (04) : 609 - 618
  • [46] Measurement of trust in human-robot collaboration
    Freedy, Amos
    DeVisser, Ewart
    Weltman, Gershon
    Coeyman, Nicole
    CTS 2007: PROCEEDINGS OF THE 2007 INTERNATIONAL SYMPOSIUM ON COLLABORATIVE TECHNOLOGIES AND SYSTEMS, 2007, : 106 - 114
  • [47] Collaboration, dialogue, and human-robot interaction
    Fong, T
    Thorpe, C
    Baur, C
    ROBOTICS RESEARCH, 2003, 6 : 255 - 266
  • [48] Multimodal Interface for Human-Robot Collaboration
    Rautiainen, Samu
    Pantano, Matteo
    Traganos, Konstantinos
    Ahmadi, Seyedamir
    Saenz, Jose
    Mohammed, Wael M.
    Lastra, Jose L. Martinez
    MACHINES, 2022, 10 (10)
  • [49] Progress and prospects of the human-robot collaboration
    Ajoudani, Arash
    Zanchettin, Andrea Maria
    Ivaldi, Serena
    Albu-Schaeffer, Alin
    Kosuge, Kazuhiro
    Khatib, Oussama
    AUTONOMOUS ROBOTS, 2018, 42 (05) : 957 - 975
  • [50] Towards Safe Human-Robot Collaboration
    Finkemeyer, Bernd
    2017 22ND INTERNATIONAL CONFERENCE ON METHODS AND MODELS IN AUTOMATION AND ROBOTICS (MMAR), 2017, : 862 - 867