面向月面与人协作的仿人臂动力学参数辨识
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1中国科学院自动化研究所多模态人工智能系统全国重点实验室,北京 100190;2中国科学院大学人工智能学院,北京 100049;3中科硅纪(南京)机器人有限公司,南京 211135

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通讯作者:

孙佳,女,副研究员,E-mail:jia.sun@ia.ac.cn。

中图分类号:

TP24

基金项目:

国家自然科学基金青年科学基金(62303454)。


Dynamic Parameter Identification of Humanoid Arm for Lunar Surface Human-Robot Collaboration
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1State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;2School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China;3CasiaHand Robotics (Nanjing) Co., Ltd., Nanjing 211135, China

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    摘要:

    为保障仿人臂在月面环境下与航天员的安全精确协同,本文以6自由度(Six-degree-of-freedom, 6-DOF)仿人臂为研究对象,在其动力学特性分析的基础上,提出了一种适用于仿人臂的动力学参数辨识方法。首先,建立仿人臂的运动学和动力学模型,在仿人臂极低速协作场景下,对仿人臂动力学模型进行简化,得到最小复合重力参数集及其对应的重力回归矩阵。其次,将重力回归矩阵参数可行域最大化作为辨识轨迹优化目标,并考虑仿人臂的运动限位和碰撞规避作为优化的约束条件。最后,分别在月面重力仿真环境和地球重力环境开展了模型的仿真和实验验证。结果表明,月面仿真辨识后的各关节计算力矩误差百分比的平均值仅为5.5%,实验验证中各关节力矩的平均绝对误差均远小于其平均噪声幅值,本文所用辨识方法建立的动力学模型能够反映仿人臂极低速运动时的动力学特性。

    Abstract:

    To ensure the safe and precise collaboration between humanoid robotic arms and astronauts in the lunar environment, this paper investigates a six-degree-of-freedom (6-DOF) humanoid arm and proposes a dynamic parameter identification method based on its dynamic characteristics. First, the kinematic and dynamic models of the humanoid arm are established. For the extremely low-speed collaborative scenarios, the dynamic model is simplified to obtain the minimal set of composite gravitational parameters and its corresponding gravity regressor matrix. Second, the trajectory optimization objective is set to maximize the feasible parameter space of the gravity regression matrix, with constraints incorporating the humanoid arm’s motion limits and collision avoidance. Finally, simulations and experiments are conducted in both a simulated lunar gravity environment and an earth gravity environment. The results show that the average percentage error of the calculated joint torques after identification is only 5.5% in the lunar simulation and the mean absolute error of the joint torques is significantly smaller than the average noise amplitude in the experimental validation. Results demonstrate that the dynamic model established by the proposed identification method can accurately reflect the dynamic characteristics of the humanoid arm during extremely low-speed motion.

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刘茜,黄亚宇,李大珩,申洲,付云瑾,孙佳,王鹏.面向月面与人协作的仿人臂动力学参数辨识[J].南京航空航天大学学报,2026,58(3):501-510

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  • 收稿日期:2026-03-03
  • 最后修改日期:2026-05-15
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  • 在线发布日期: 2026-06-18
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