抓住
假手
滑倒
触觉技术
计算机科学
机械手
计算机视觉
人工智能
视觉反馈
机器人
模拟
人机交互
工程类
机械工程
程序设计语言
作者
Li Jiang,Ning Zhang,Yang Li,Bo Zeng,Li Jiang
标识
DOI:10.1109/tnsre.2022.3231972
摘要
Stable grasping without slips or crushing is a major challenge for amputees who lose the natural sensorimotor system in dynamically changing daily life environments. Amputees rely largely on visual cues to control the prosthetic hand to complete daily living activities due to a lack of haptic feedback. The human tactile sense can simultaneously feel normal and shear forces. When grasping objects based on the anticipated load conditions, the human hand adjusts the grasping force in real time based on shear force feedback. Here, a sensorimotor-inspired grasping strategy for a dexterous prosthetic hand is proposed to improve grasping performance. The proposed grasping strategy allows the amputee to intuitively control the prosthetic hand. The dexterous prosthetic hand can adaptively adjust the grasp force based on tactile sensory feedback to simultaneously prevent the slipping of objects with unknown shapes, weight, roughness, and softness. Experiments show that the myoelectrical prosthetic hand has grasping force adaptive adjustment and slip prevention ability and provides improved grasping compared to prosthetics with traditional open-loop control.
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