On-line parameter adaptation for a momentum control in the post-grasping of a tumbling target with model uncertainty

Satoko Abiko, Gerd Hirzinger

    研究成果: Conference contribution

    28 引用 (Scopus)

    抜粋

    This paper addresses an on-line parameter adaptation for a momentum accumulation control of a space robot in the post-grasping of a tumbling target whose dynamic parameters are unknown a priori. The model inaccuracies in the target lead to an unexpected tumbling motion after grasping a target. It is desired to transfer the entire angular momentum to the reaction wheels as quickly as possible while stabilization trajectory of the robot-arm is tracked to avoid self-collision in the chaser-robot. Firstly, we derive a momentum control method from the angular momentum equation to accumulate the entire angular momentum into the reaction wheels. The parameter inaccuracies degrade the control performance. Then, an online adaptation law by using coupling force and momentum is proposed. A numerical simulation is carried out to verify the operational performance of the proposed method in the presence of model uncertainty.

    元の言語English
    ホスト出版物のタイトルProceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
    ページ847-852
    ページ数6
    DOI
    出版物ステータスPublished - 2007 12 1
    イベント2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007 - San Diego, CA, United States
    継続期間: 2007 10 292007 11 2

    出版物シリーズ

    名前IEEE International Conference on Intelligent Robots and Systems

    Other

    Other2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
    United States
    San Diego, CA
    期間07/10/2907/11/2

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Software
    • Computer Vision and Pattern Recognition
    • Computer Science Applications

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  • これを引用

    Abiko, S., & Hirzinger, G. (2007). On-line parameter adaptation for a momentum control in the post-grasping of a tumbling target with model uncertainty. : Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007 (pp. 847-852). [4399190] (IEEE International Conference on Intelligent Robots and Systems). https://doi.org/10.1109/IROS.2007.4399190