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A collaborative learning optimization strategy for shared control of walking-aid robot

  • Wenxia Xu
  • , Jian Huang*
  • , Yongji Wang
  • , Chunjing Tao
  • *Corresponding author for this work
  • Huazhong University of Science and Technology
  • National Research Center for Rehabilitation Technical Aids

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Elderly and disabled people often require assistance in getting about with maximum freedom and control while maintaining overall safety. In this chapter, we develop a collaborative learning optimization strategy for shared control of an intelligent walking-aid robot for the purpose of assisting elderly and disabled people. The proposed architecture can adjust two user control weights dynamically by a learning algorithm according to user control habit and walking environment, allowing both human and robot to maintain control of the walking-aid robot. Finally, the experiment results illustrate the validity of the collaborative learning optimization strategy as part of a shared control algorithm.

Original languageEnglish
Title of host publicationApplied Methods and Techniques for Mechatronic Systems
Subtitle of host publicationModelling, Identification and Control
PublisherSpringer Verlag
Pages411-423
Number of pages13
ISBN (Print)9783642363849
DOIs
StatePublished - 2014
Externally publishedYes

Publication series

NameLecture Notes in Control and Information Sciences
Volume452
ISSN (Print)0170-8643

Keywords

  • Collaborative learning
  • Sarsa-learning
  • Shared control
  • Walking-aid robot

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