Gravity-induced extra moments may cause the robotic arm to drop things with an unequal mass distribution. In order to address this issue, we provide a unique technique, which extra wrists and touch sensors or a huge number of tests are not needed. As a first step, we measure the rod object’s center of mass using the robot arm’s commonly fixed joint torque sensors and RGBD cameras. The approach for improving the stability of grasping is also provided. In “Mujoco,” simulation experiments are undertaken. Results indicate that our efforts to improve gripping robustness have been successful.


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    Titel :

    Center-of-Mass-Based Robust Grasp Pose Adaptation Using RGBD Camera and Force/Torque Sensing


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Yan, Liang (Herausgeber:in) / Duan, Haibin (Herausgeber:in) / Deng, Yimin (Herausgeber:in) / Liu, Shang (Autor:in) / Wei, Xiaobao (Autor:in) / Wang, Lulu (Autor:in) / Zhang, Jing (Autor:in) / Li, Boyu (Autor:in) / Yue, Haosong (Autor:in)

    Kongress:

    International Conference on Guidance, Navigation and Control ; 2022 ; Harbin, China August 05, 2022 - August 07, 2022



    Erscheinungsdatum :

    2023-01-31


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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