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Evolving Systems

, Volume 9, Issue 1, pp 43–56 | Cite as

A fuzzy approach towards inductive transfer and human–machine interface control design

  • Rui Azevedo Antunes
  • Luís Brito Palma
  • Fernando Vieira Coito
  • Hermínio Duarteramos
Original Paper

Abstract

Traditional machines do not adapt to their operators, instead they implicitly demand human adaptation. Human adaptive mechatronics (HAM) is the research topic that covers the design of devices and controllers for assisting the human. HAM devices are capable to measure and estimate the operator’s skill/dexterity, while a real-time assist-controller enhances machine adaptation, improving the overall human–machine performance. Nowadays, the demand for such devices has particular potential in many activities, which involve manual operations, such as in assistive technology. The main contribution of this work is the proposal of a fuzzy clustering methodology to the development of a real-time inductive transfer embedded controller, used for improving the operator’s proficiency, under a human-in-the-loop environment relying on visual feedback information. Other contribution is the proposal of a condition for inductive transfer between human operators, based on correlation analysis. The operator behaviour is modelled and enhanced from a human–machine interface fuzzy classifier and assisting scheme, which uses real-time data and additional information collected from an expert user. Experimental tests were performed by different participants under a driving simulator, for evaluation of the proposed methodology. The fuzzy clustering approach confirmed to significantly improve the transfer learning and the driving skills of the human operators.

Keywords

Inductive transfer Fuzzy clustering Human machine interaction Correlation analysis Embedded control Performance evaluation 

Notes

Acknowledgements

This work has been supported by Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa, by CTS-Uninova research unit, by Escola Superior de Tecnologia de Setúbal do Instituto Politécnico de Setúbal and by national funds through FCT-Fundação para a Ciência e a Tecnologia within the research unit CTS-Centro de Tecnologia e Sistemas (project UID/EEA/00066/2013). The authors would like to thank all the institutions and all the participants in the driving experiments.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Rui Azevedo Antunes
    • 1
  • Luís Brito Palma
    • 2
  • Fernando Vieira Coito
    • 2
  • Hermínio Duarteramos
    • 2
  1. 1.Department of Electrical Engineering, Escola Superior de Tecnologia de SetúbalInstituto Politécnico de SetúbalSetúbalPortugal
  2. 2.Department of Electrical Engineering, Faculdade de Ciências e TecnologiaUniversidade Nova de LisboaCaparicaPortugal

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