Tigue James A, King Raymond J, Mascaro Stephen A
Department of Mechanical Engineering, University of Utah, 1495 E. 100 S, Salt Lake City, UT 84112 e-mail:
Mem. ASME Department of Mechanical Engineering, University of Utah, 1495 E. 100 S, Salt Lake City, UT 84112 e-mail:
J Dyn Syst Meas Control. 2020 Mar 1;142(3):0310071-3100714. doi: 10.1115/1.4045494. Epub 2019 Dec 23.
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.
本文旨在使用键合图建模来创建迄今为止最全面的手指肌腱模型并进行仿真。当前的模型要么限于无外部接触的自由运动，要么限于肌腱与指尖之间固定的手指力传递。在这项工作中提出的正向动力学模型，在给定手指肌腱输入的情况下，同时模拟中央手指的肌腱 - 手指运动学和接触力。从键合图导出的模型方程伴随着对力臂、肌腱松弛和关节运动范围（ROM）的解剖复杂性进行建模的非线性关系。该模型的结构使用机器人试验台——犹他州解剖学正确机器人试验台（UART）手指进行了验证。使用键合图模型模拟了UART手指在自由运动（无外部接触）和表面接触期间的实验运动。还模拟了表面接触实验期间的接触力。平均而言，该模型能够在自由运动和表面接触实验中预测手指的稳态姿势，关节角度误差小于6°。静态接触力得到了准确预测，平均力大小误差为11.5%，平均方向误差为12°。
