A Deep Learning Approach for Position Control of a Mobile Robot

The study presents an innovative method for decoding the brain signals of subjects to control a Khepera IV mobile robot, thereby providing assistance to those with neuro-motor disorders. The afore-said objective is accomplished through a novel Convolutional Neural Network (CNN) that precisely classi...

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Bibliographic Details
Published in2023 8th International Conference on Computers and Devices for Communication (CODEC) pp. 1 - 2
Main Authors Datta, Srirupa, Sengupta, Swapnil, Das, Tamodip, Dasgupta, Sourya, Ghosh, Sayantani, Konar, Amit
Format Conference Proceeding
LanguageEnglish
Published IEEE 14.12.2023
Subjects
Codecs
Computer architecture
Computers
convolutional neural network
Deep learning
EEG
Legged locomotion
motor imagery
Motors
Position control
short time fourier transform
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Summary:The study presents an innovative method for decoding the brain signals of subjects to control a Khepera IV mobile robot, thereby providing assistance to those with neuro-motor disorders. The afore-said objective is accomplished through a novel Convolutional Neural Network (CNN) that precisely classifies four motor imagination labels (left hand, right hand, left leg, and right leg) corresponding to four Khepera robot maneuvers (left, right, forward, and backward).
DOI:10.1109/CODEC60112.2023.10466131