Motion and visual control for an upper-limb exoskeleton robot via learning

Jian Bin Huang, I. Yu Lin, Kuu-Young Young*, Chun Hsu Ko

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The arrival of an aging society brings up many challenges, including the demanding need in medical resources. In responding, the exoskeleton robot becomes one of the focuses, which provides assistance for people with locomotive problems. Motivated by it, our laboratory has developed a wearable upper-limb exoskeleton robot, named as HAMEXO. It is of 2 DOF and intended to provide motion assistance for users in their daily activities. To serve the purpose, HAMEXO is equipped with a visual system to detect objects in the environment, and also a motion controller for its governing. To deal with the coupling involved during the movements of the two joints and the need to adapt to various users, we adopted the learning approach for controller design. Experiments are performed to demonstrate its effectiveness.

Original languageEnglish
Title of host publicationAdvances in Neural Networks - ISNN 2017 - 14th International Symposium, ISNN 2017, Proceedings
EditorsFengyu Cong, Qinglai Wei, Andrew Leung
PublisherSpringer Verlag
Number of pages8
ISBN (Print)9783319590806
StatePublished - 1 Jan 2017
Event14th International Symposium on Neural Networks, ISNN 2017 - Sapporo, Hakodate, and Muroran, Hokkaido, Japan
Duration: 21 Jun 201726 Jun 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10262 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th International Symposium on Neural Networks, ISNN 2017
CitySapporo, Hakodate, and Muroran, Hokkaido


  • Learning
  • Motion and visual control
  • Upper-limb exoskeleton robot

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