Implementing gait pattern control and transition for legged locomotion

Conference paper

Yang, Z., Rocha, M., Lima, P., Karamanoglu, M. and Franca, F. 2014. Implementing gait pattern control and transition for legged locomotion. 27th International Conference on CADCAM, Robotics and Factories of the Future 2014. London, United Kingdom 22 - 24 Jul 2014 IOP Publishing. pp. 1-7 https://doi.org/10.1088/1757-899X/65/1/012008
TypeConference paper
TitleImplementing gait pattern control and transition for legged locomotion
AuthorsYang, Z., Rocha, M., Lima, P., Karamanoglu, M. and Franca, F.
Abstract

In this work, a generalised central pattern generator (CPG) model is formulated to generate a full range of gait patterns for a hexapod insect. To this end, a recurrent neuronal network module, as the building block for rhythmic patterns, is proposed to extend the concept of oscillatory building blocks (OBB) for constructing a CPG model. The model is able to make transitions between different gait patterns by simply adjusting one model parameter. Simulation results are further presented to show the effectiveness and performance of the CPG network.

Conference27th International Conference on CADCAM, Robotics and Factories of the Future 2014
Page range1-7
Proceedings Title27th International Conference on CADCAM, Robotics and Factories of the Future 2014 22–24 July 2014, London, UK
SeriesIOP Conference Series-Materials Science and Engineering
ISSN1757-8981
Electronic1757-899X
PublisherIOP Publishing
Publication dates
Print22 Jul 2014
Publication process dates
Deposited28 May 2015
CompletedJul 2014
Output statusPublished
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Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Published under licence by IOP Publishing Ltd

Web address (URL)http://iopscience.iop.org/1757-899X/65/1/012008/pdf/1757-899X_65_1_012008.pdf
Digital Object Identifier (DOI)https://doi.org/10.1088/1757-899X/65/1/012008
Web of Science identifierWOS:000340247700008
LanguageEnglish
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