Tang Rongrong, Yang Qianqian, Song Rong
The Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China.
The Shenzhen Research Institute, Sun Yat-sen University, Guangzhou, China.
Front Neurorobot. 2022 Mar 3;16:850692. doi: 10.3389/fnbot.2022.850692. eCollection 2022.
To obtain an anthropomorphic performance in physical human-robot interaction during a reaching task, a variable impedance control (vIC) algorithm with human-like characteristics is proposed in this article. The damping value of the proposed method is varied with the target position as well as through the tracking error. The proposed control algorithm is compared with the impedance control algorithm with constant parameters (IC) and another vIC algorithm, which is only changed with the tracking error (vIC-e). The different control algorithms are validated through the simulation study, and are experimentally implemented on a cable-driven rehabilitation robot. The results show that the proposed vIC can improve the tracking accuracy and trajectory smoothness, and reduce the interaction force at the same time.
为了在伸手任务期间的人机物理交互中获得拟人化性能，本文提出了一种具有类人特性的可变阻抗控制（vIC）算法。该方法的阻尼值随目标位置以及跟踪误差而变化。将所提出的控制算法与具有恒定参数的阻抗控制算法（IC）以及另一种仅随跟踪误差变化的vIC算法（vIC-e）进行比较。通过仿真研究验证了不同的控制算法，并在缆索驱动的康复机器人上进行了实验实现。结果表明，所提出的vIC可以提高跟踪精度和轨迹平滑度，同时降低相互作用力。
