Abstract
To achieve strength augmentation, endurance enhancement, and human assistance in a functional autonomous exoskeleton, control precision, back drivability, low output impedance, and mechanical compactness are desired. In our previous work, two elastic modules were designed for human–robot interaction sensing and compliant control, respectively. According to the intrinsic sensing properties of the elastic module, in this paper, only one compact elastic module is applied to realize both purposes. Thus, the corresponding control strategy is required and evolving internal model control is proposed to address this issue. Moreover, the input signal to the controller is derived from the deflection of the compact elastic module. The human–robot interaction is considered as the disturbance which is approximated by the output error between the exoskeleton control plant and evolving forward learning model. Finally, to verify our proposed control scheme, several experiments are conducted with our robotic exoskeleton system. The experiment shows a satisfying result and promising application feasibility.
Highlights
In the past two decades, several types of prostheses, orthoses, and exoskeletons have been developed to meet the demand for human-limb assistance [1,2,3], interface of virtual reality [4,5], and strength augmentation [6] owing to dramatic progress in computing, sensing, as well as control.various studies have been devoted to developing novel compact mechanical structures and corresponding control methodologies.To follow the human intention efficiently, the sensing system should provide full information for the exoskeleton controller
Since our task is to follow the human motion in real-time, the exoskeleton tries to track the joint motion according to the deflection of the elastic module measured by the encoder
Since the forward model is learned for the exoskeleton dynamic model and evolved online, the control scheme should be efficient for any human subject
Summary
In the past two decades, several types of prostheses, orthoses, and exoskeletons have been developed to meet the demand for human-limb assistance [1,2,3], interface of virtual reality [4,5], and strength augmentation [6] owing to dramatic progress in computing, sensing, as well as control. To follow the human intention efficiently (i.e., discrete or rhythmic movements), the sensing system should provide full information for the exoskeleton controller. Assistive Limb exoskeleton [7] focuses on the electromyographical (EMG) signals. The human intention is collected by applying a pattern recognition technique. The main limitation is that the EMG signals suffer heavily from unwanted noise and overlap of the spectrum with other signals
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