Detecting and preventing slip is a major challenge in robotic hand operation, underpinning the robot's ability to perform safe and reliable grasps. Using the robotic hand design from the authors' earlier work, a sensing and control strategy is proposed here to prevent object slippage. The robotic hand is cable-driven, single-actuated, has five fingers, and is capable of replicating most human hand motions. The slip sensing approach utilizes a piezoelectric vibration sensor, namely, polyvinylidene fluoride (PVDF), which is a flexible, thin, cheap, and highly sensitive material. The power of the filtered PVDF signal is shown to exhibit identifiable signatures during slip, thus providing a suitable slip detection mechanism. Using the PVDF feedback, an integral controller is implemented to prevent the grasped object from falling and ensure a safe, powerful, and reliable grasp. The extension movement of the robotic hand is controlled using a bend sensor, through a proportional-integral (PI) controller. The robotic hand weights 338 gr. The functionality and robustness of the proposed slip-detection sensory system and control logic implementation are evaluated through experiments.
A Soft High Force Hand Exoskeleton for Rehabilitation and Assistance of Spinal Cord Injury and Stroke Individuals
Icahn School of Medicine at Mount Sinai(西奈山伊坎医学院);Grove School of Engineering(格罗夫工程学院);City College of New York(纽约城市学院);Moss Rehabilitation Research Institute(莫斯康复研究所);University of Wisconsin-Madison(威斯康星大学麦迪逊分校)
Development of a 15-Degree-of-Freedom Bionic Hand with Cable-Driven Transmission and Distributed Actuation
Department of Computer Science and Engineering, Shanghai Jiao Tong University(计算机科学与工程系,上海交通大学);Department of Engineering Mechanics, Shanghai Jiao Tong University(工程力学系,上海交通大学);Department of Automation, Shanghai Jiao Tong University(自动化系,上海交通大学);Department of Automation, Key Laboratory of System Control and Information Processing of Ministry of Education, Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education, Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai Jiao Tong University(自动化系,教育部系统控制与信息处理重点实验室,教育部海洋智能设备与系统重点实验室,智能控制与管理工程研究中心,上海交通大学)