More than 50 million people worldwide have permanent hand injuries due to stroke, spinal cord injury, and physical injury. Hand motor dysfunction makes patients lose their ability to take care of themselves and seriously reduces their quality of life. However, the existing hand assistive devices have a single function and cannot actively provide assistive force. Therefore, it is of great significance to study hand-assisted exoskeleton robots to assist patients in completing operations on daily objects. Based on this background, this paper focuses on the system design of the hand-assisted exoskeleton robot, the quantitative evaluation of the assistance effect, the passive human-robot interaction control, and the active human-robot interaction control. The main work and innovations of this paper are summarized as follows:
A hand exoskeleton capable of assisting index finger and thumb grasping is designed, and the grasping dexterity of the mechanism is analyzed, and guarantees the effectiveness of the grip. According to literature statistics, the human hand inadvertently makes thousands of grasps daily. To ensure that the hand exoskeleton has the same grasping ability, a three-motor-driven hand exoskeleton based on link transmission is designed in this paper. Aiming at the grasping characteristics of fingers, an underactuated mechanism based on redundant degrees of freedom is proposed to realize the adaptive grasping of objects of different shapes and sizes by the exoskeleton. The kinematics and statics of the underactuated mechanism are established, the grasping dexterity of the mechanism is analyzed, and an optimization method of exoskeleton grasping force based on a multi-objective genetic algorithm is proposed to ensure the grasping stability. Finally, the motion transparency and grasping dexterity experiments are carried out on the hand exoskeleton prototype. The experimental results show that the proposed exoskeleton can help the wearer to grasp different objects and has grasping dexterity.
A framework for evaluating the effectiveness of hand-assisted exoskeletons based on human motion, human physiology, and human feelings is proposed, which realizes the quantitative evaluation of the function of hand-assisted exoskeletons. Evaluating the effectiveness of a hand exoskeleton function has implications for both hand exoskeleton improvement and user usage. This paper proposes to establish a quantitative evaluation method for the effectiveness of hand exoskeletons from three levels of human movement, physiology and feelings, and designs five indicators to quantitatively evaluate the designed exoskeleton. At the same time, an experimental paradigm for the functional verification of the hand-assisted exoskeleton is constructed. Finally, the feasibility of the proposed framework for evaluating the effectiveness of the power-assisted exoskeleton is proved by experiments, and the designed hand-assisted exoskeleton can be close to the natural grasping motion of the human hand and reduce the wearer's force and muscle fatigue.
It is proposed that a hybrid method of active disturbance rejection control of hand exoskeleton based on reduced-order extended state observer and compliant control based on admittance control to ensure the safety of human-robot interaction. In this paper, aiming at the difficult problem of dynamic modeling of the coupled system of human hand exoskeleton and the problem of poor anti-disturbance performance of traditional PID control, an active disturbance rejection controller based on extended state observer is designed to realize the position control of the power-assisted exoskeleton, and the controller is analyzed. stable transient performance, and the bounded input bounded output stability of the controller is demonstrated. At the same time, the active disturbance rejection controller based on the reduced-order extended state observer is also designed, and the internal relationship between the two controllers is analyzed. Finally, the anti-disturbance performance and anti-noise ability of the two controllers are compared. In addition, this paper also designs a hand exoskeleton controller based on admittance control, which ensures the flexibility of human-robot interaction. Finally, the anti-disturbance performance and compliance performance of the proposed control methods are verified by experiments.
A voluntary control method is proposed based on the sEMG-driven musculoskeletal model to realize the voluntary control of the user's exoskeleton in the dynamic grasping task scenario. Aiming at the problem of poor personalization of the current hand exoskeleton assistance strategy, this paper firstly establishes a neuromusculoskeletal model based on the Hill model, and obtains a personalized musculoskeletal model through experimental calibration. In this paper, a method for estimating finger joint torque of subjects based on sEMG-driven personalized musculoskeletal model is proposed, and then an exoskeleton controller based on admittance control is designed to realize the user's voluntary control of the exoskeleton to assist its grasping. Voluntary control methods adjust the degree of exoskeleton assistance by evaluating the user's voluntary effort. Finally, the effectiveness of the personalization and voluntary control method of the assistive strategy is verified by experiments.
|Sub direction classification||智能机器人|
|planning direction of the national heavy laboratory||先进智能应用与转化|
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