基于键合图和机器人验证的人体手指肌腱系统同步运动和接触力建模。

James A Tigue, Raymond J King, Stephen A Mascaro
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引用次数: 3

摘要

本文旨在利用键合图建模建立迄今为止最全面的手指肌腱模型和仿真。目前的模型要么局限于无外部接触的自由运动,要么局限于肌腱和指尖之间的固定手指力传递。在这项工作中提出的正向动力学模型,同时模拟了给定手指肌腱输入的中心手指的肌腱-手指运动和接触力的运动学。由键合图导出的模型方程伴随着非线性关系,模拟了力臂、肌腱松弛和关节活动范围(ROM)的解剖复杂性。模型的结构使用机器人试验台,犹他州的解剖正确机器人试验台(UART)手指进行验证。利用键合图模型模拟了UART手指在自由运动(无外部接触)和表面接触时的实验运动。模拟了表面接触实验过程中的接触力。在自由运动和表面接触实验中,平均而言,该模型能够预测手指关节角误差小于6度的稳态姿态。静态接触力预测精度高,力量级误差平均为11.5%,方向误差平均为12°。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simultaneous Kinematic and Contact Force Modeling of a Human Finger Tendon System Using Bond Graphs and Robotic Validation.

This paper aims to use bond graph modeling to create the most comprehensive finger tendon model and simulation to date. Current models are limited to either free motion without external contact or fixed finger force transmission between tendons and fingertip. The forward dynamics model, presented in this work, simultaneously simulates the kinematics of tendon-finger motion and contact forces of a central finger given finger tendon inputs. The model equations derived from bond graphs are accompanied by nonlinear relationships modeling the anatomical complexities of moment arms, tendon slacking, and joint range of motion (ROM). The structure of the model is validated using a robotic testbed, Utah's Anatomically correct Robotic Testbed (UART) finger. Experimental motion of the UART finger during free motion (no external contact) and surface contact are simulated using the bond graph model. The contact forces during the surface contact experiments are also simulated. On average, the model was able to predict the steady-state pose of the finger with joint angle errors less than 6 deg across both free motion and surface contact experiments. The static contact forces were accurately predicted with an average of 11.5% force magnitude error and average direction error of 12 deg.

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