Xu Xiaolei, Deng Hua, Zhang Yi, Yi Nianen
State Key Laboratory of Precision Manufacturing for Extreme Service Performance, Central South University, Changsha 410083, China.
College of Mechanical & Electrical Engineering, Central South University, Changsha 410083, China.
Biomimetics (Basel). 2024 Oct 27;9(11):658. doi: 10.3390/biomimetics9110658.
Human muscles can generate force and stiffness during contraction. When in contact with objects, human hands can achieve compliant grasping by adjusting the grasping force and the muscle stiffness based on the object's characteristics. To realize humanoid-compliant grasping, most prosthetic hands obtain the stiffness parameter of the compliant controller according to the environmental stiffness, which may be inconsistent with the amputee's intention. To address this issue, this paper proposes a compliant grasp control method for an underactuated prosthetic hand that can directly obtain the control signals for compliant grasping from surface electromyography (sEMG) signals. First, an estimation method of the grasping force is established based on the Huxley muscle model. Then, muscle stiffness is estimated based on the muscle contraction principle. Subsequently, a relationship between the muscle stiffness of the human hand and the stiffness parameters of the prosthetic hand controller is established based on fuzzy logic to realize compliant grasp control for the underactuated prosthetic hand. Experimental results indicate that the prosthetic hand can adjust the desired force and stiffness parameters of the impedance controller based on sEMG, achieving a quick and stable grasp as well as a slow and gentle grasp on different objects.
人类肌肉在收缩过程中能够产生力量和刚度。当与物体接触时,人类的手可以根据物体的特性通过调整抓握力和肌肉刚度来实现柔顺抓握。为了实现仿人柔顺抓握,大多数假肢手根据环境刚度获取柔顺控制器的刚度参数,这可能与截肢者的意图不一致。为了解决这个问题,本文提出了一种用于欠驱动假肢手的柔顺抓握控制方法,该方法可以直接从表面肌电(sEMG)信号中获取柔顺抓握的控制信号。首先,基于赫胥黎肌肉模型建立抓握力的估计方法。然后,根据肌肉收缩原理估计肌肉刚度。随后,基于模糊逻辑建立人手肌肉刚度与假肢手控制器刚度参数之间的关系,以实现对欠驱动假肢手的柔顺抓握控制。实验结果表明,该假肢手能够基于sEMG调整阻抗控制器的期望力和刚度参数,在不同物体上实现快速稳定的抓握以及缓慢轻柔的抓握。