loading
Papers

Research.Publish.Connect.

Paper

Authors: Guilherme Barros Castro 1 ; Kazuya Tamura 2 ; Atsuo Kawamura 2 and André Hirakawa 1

Affiliations: 1 University of São Paulo, Brazil ; 2 Yokohama National University, Japan

ISBN: 978-989-758-220-2

Keyword(s): Biologically-Inspired Neural Network, Humanoid Robots, Computational Intelligence, Walking Stabilization.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Reactive AI ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: In order to accomplish desired tasks, humanoid robots may have to deal with unpredicted disturbances, generated by objects, people and even ground imperfections. In some of these cases, foot placement is critical and cannot be changed. Furthermore, the robot has to conduct the actions planned meanwhile stabilizing its walking motion. Therefore, we propose a Biologically-inspired Neural Network (BiNN) to stabilize the walking motion of humanoid robots by ankle joint control, which minimally affects the current movements of the robot. In contrast to other neural networks, which only generate walking patterns, the BiNN is adaptive, as it compensates disturbances during the robot motion. Moreover, the BiNN has a low computational time and can be used as a module of other control methods. This approach was evaluated with Webots simulator, presenting improvements in the compensation of an external force in regard to its magnitude and duration.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.229.122.219

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Castro, G.; Tamura, K.; Kawamura, A. and Hirakawa, A. (2017). Biologically-Inspired Neural Network for Walking Stabilization of Humanoid Robots.In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-220-2, pages 96-104. DOI: 10.5220/0006138700960104

@conference{icaart17,
author={Guilherme Barros Castro. and Kazuya Tamura. and Atsuo Kawamura. and André Hirakawa.},
title={Biologically-Inspired Neural Network for Walking Stabilization of Humanoid Robots},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2017},
pages={96-104},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006138700960104},
isbn={978-989-758-220-2},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Biologically-Inspired Neural Network for Walking Stabilization of Humanoid Robots
SN - 978-989-758-220-2
AU - Castro, G.
AU - Tamura, K.
AU - Kawamura, A.
AU - Hirakawa, A.
PY - 2017
SP - 96
EP - 104
DO - 10.5220/0006138700960104

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.