Abstract
Exoskeleton system which is to assist the motion of physically weak persons such as disabled, injured and elderly persons is discussed in this paper. The proposed exoskeletons are controlled basically based on the electromoyogram (EMG) signals. And a mind model is constructed to identify person’s mind for predicting or estimating person’s behavior. The proposed mind model is installed in an exoskeleton power assistive system named IAE for walking aid. The neural-network is also be used in this system to help learning. The on-line learning adjustment algorithm based on multi-sensor that are fixed on the robot is designed which makes the locomotion stable and adaptable.
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© 2006 Springer-Verlag Berlin Heidelberg
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Cao, H., Yin, Y., Du, D., Lin, L., Gu, W., Yang, Z. (2006). Neural-Network Inverse Dynamic Online Learning Control on Physical Exoskeleton. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893295_77
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DOI: https://doi.org/10.1007/11893295_77
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46484-6
Online ISBN: 978-3-540-46485-3
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