Adaptation of human motion capture data to humanoid robots for motion imitation using optimization

被引:0
|
作者
Intelligent Robotics Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650, Korea, Republic of [1 ]
机构
来源
Integr. Comput. Aided Eng. | 2006年 / 4卷 / 377-389期
关键词
Human computer interaction - Kinematics - Motion estimation - Optimization;
D O I
10.3233/ica-2006-13406
中图分类号
学科分类号
摘要
The interactions between a humanoid robot and human are important, when the humanoid robot is requested to serve people with human-friendly services. For such interactions, the imitation of human arm motions by a humanoid robot is discussed as the first step for imitating the full body motion of a human. The human motions captured by a motion capture system may not be applied directly to the humanoid robot because of the differences in geometric aspect, dynamics and kinematic capabilities between the robot and human. To overcome this difficulty, a method to adapt captured motions to the humanoid robot is developed. The geometric difference in the arm length is resolved by scaling the arm length of the robot with a constant based on a length ratio. The imitation of human arm motion is then realized by solving an inverse kinematics problem which is formulated as an optimization task. The errors between the captured trajectories of human arms and the approximated trajectories of robot's arms are minimized. The dynamics capabilities of the joint motors such as limits of joint position and velocity, are imposed on the optimization problem. Several human motions are imitated by the humanoid robots developed in our institute. © 2006 - IOS Press and the authors(s). All rights reserved.
引用
收藏
相关论文
共 50 条
  • [21] A motion imitation system for humanoid robots with inference-based optimization and an auditory user interface
    Hideaki Itoh
    Nozomi Ihara
    Hisao Fukumoto
    Hiroshi Wakuya
    Artificial Life and Robotics, 2020, 25 : 106 - 115
  • [22] Human Motion Imitation for Humanoid by Recurrent Neural Network
    Kim, Mingon
    Kim, Sanghyun
    Park, Jaeheung
    2016 13TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAI), 2016, : 519 - 520
  • [23] Improved Motion Planning of Humanoid Robots Using Bacterial Foraging Optimization
    Muni, Manoj Kumar
    Parhi, Dayal R.
    Kumar, Priyadarshi Biplab
    ROBOTICA, 2021, 39 (01) : 123 - 136
  • [24] Interaction Mesh Based Motion Adaptation for Biped Humanoid Robots
    Nakaoka, Shin'ichiro
    Komura, Taku
    2012 12TH IEEE-RAS INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS (HUMANOIDS), 2012, : 625 - 631
  • [25] Humanoid motion design considering rhythm based on human motion capture
    Zhang, Lige
    Huang, Qiang
    Lv, Shusheng
    Shi, You
    Wang, Zhijie
    Jafri, Ali Raza
    2006 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-12, 2006, : 2491 - +
  • [26] Design of humanoid complicated dynamic motion based on human motion capture
    Huang, Q
    Peng, ZQ
    Zhang, WM
    Zhang, LG
    Li, KJ
    2005 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-4, 2005, : 686 - 691
  • [27] Design and similarity evaluation on humanoid motion based on human motion capture
    Huang, Qiang
    Yu, Zhangguo
    Zhang, Weimin
    Xu, Wei
    Chen, Xuechao
    ROBOTICA, 2010, 28 : 737 - 745
  • [28] Optimal control strategy for real-time motion imitation of humanoid robots
    Han, Ke
    Li, Shiqi
    Zhou, Yumei
    Xiong, Youjun
    Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition), 2023, 51 (11): : 1 - 8
  • [29] Control-Aware Mapping of Human Motion Data with Stepping for Humanoid Robots
    Yamane, Katsu
    Hodgins, Jessica
    IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010), 2010, : 726 - 733
  • [30] A humanoid robot with motion imitation ability
    Chou, Li-Po
    Wang, Wen-June
    PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2007, : 2031 - 2036