Head stabilization based on a feedback error learning in a humanoid robot

Egidio Falotico, Nino Cauli, Kenji Hashimoto, Przemyslaw Kryczka, Atsuo Takanishi, Paolo Dario, Alain Berthoz, Cecilia Laschi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

In this work we propose an adaptive model for the head stabilization based on a feedback error learning (FEL). This model is capable to overcome the delays caused by the head motor system and adapts itself to the dynamics of the head motion. It has been designed to track an arbitrary reference orientation for the head in space and reject the disturbance caused by trunk motion. For efficient error learning we use the recursive least square algorithm (RLS), a Newton-like method which guarantees very fast convergence. Moreover, we implement a neural network to compute the rotational part of the head inverse kinematics. Verification of the proposed control is conducted through experiments with Matlab SIMULINK and a humanoid robot SABIAN.

Original languageEnglish
Title of host publication2012 IEEE RO-MAN
Subtitle of host publicationThe 21st IEEE International Symposium on Robot and Human Interactive Communication
Pages449-454
Number of pages6
DOIs
Publication statusPublished - 2012 Dec 14
Event2012 21st IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2012 - Paris, France
Duration: 2012 Sep 92012 Sep 13

Publication series

NameProceedings - IEEE International Workshop on Robot and Human Interactive Communication

Conference

Conference2012 21st IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2012
CountryFrance
CityParis
Period12/9/912/9/13

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ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Human-Computer Interaction

Cite this

Falotico, E., Cauli, N., Hashimoto, K., Kryczka, P., Takanishi, A., Dario, P., Berthoz, A., & Laschi, C. (2012). Head stabilization based on a feedback error learning in a humanoid robot. In 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication (pp. 449-454). [6343793] (Proceedings - IEEE International Workshop on Robot and Human Interactive Communication). https://doi.org/10.1109/ROMAN.2012.6343793