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Brain–Machine Interface and Visual Compressive Sensing-Based Teleoperation Control of an Exoskeleton Robot

Shiyuan Qiu, Zhijun Li, Wei He, Longbin Zhang, Chenguang Yang, Chun-Yi Su

IEEE Transactions on Fuzzy Systems, Volume: 25, Issue: 1, Pages: 58 - 69

Swansea University Author: Chenguang Yang

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DOI (Published version): 10.1109/TFUZZ.2016.2566676

Abstract

This paper presents a teleoperation control for an exoskeleton robotic system based on the brain-machine interface and vision feedback. Vision compressive sensing, brain-machine reference commands, and adaptive fuzzy controllers in joint-space have been effectively integrated to enable the robot per...

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Published in: IEEE Transactions on Fuzzy Systems
ISSN: 1063-6706 1941-0034
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa28341
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Abstract: This paper presents a teleoperation control for an exoskeleton robotic system based on the brain-machine interface and vision feedback. Vision compressive sensing, brain-machine reference commands, and adaptive fuzzy controllers in joint-space have been effectively integrated to enable the robot performing manipulation tasks guided by human operator's mind. First, a visual-feedback link is implemented by a video captured by a camera, allowing him/her to visualize the manipulator's workspace and movements being executed. Then, the compressed images are used as feedback errors in a nonvector space for producing steady-state visual evoked potentials electroencephalography (EEG) signals, and it requires no prior information on features in contrast to the traditional visual servoing. The proposed EEG decoding algorithm generates control signals for the exoskeleton robot using features extracted from neural activity. Considering coupled dynamics and actuator input constraints during the robot manipulation, a local adaptive fuzzy controller has been designed to drive the exoskeleton tracking the intended trajectories in human operator's mind and to provide a convenient way of dynamics compensation with minimal knowledge of the dynamics parameters of the exoskeleton robot. Extensive experiment studies employing three subjects have been performed to verify the validity of the proposed method.
Keywords: Fuzzy logic system; Teleoperation; Visual compress sense; EEG; Brain-machine interface; Exoskeleton robot
College: Faculty of Science and Engineering
Issue: 1
Start Page: 58
End Page: 69

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