Prescription of rhythmic patterns for legged locomotion

Article


Yang, Z., Zhang, D., Rocha, M., Lima, P., Karamanoglu, M. and Franca, F. 2017. Prescription of rhythmic patterns for legged locomotion. Neural Computing and Applications. 28 (11), pp. 3587-3601. https://doi.org/10.1007/s00521-016-2237-4
TypeArticle
TitlePrescription of rhythmic patterns for legged locomotion
AuthorsYang, Z., Zhang, D., Rocha, M., Lima, P., Karamanoglu, M. and Franca, F.
Abstract

As the engine behind many life phenomena, motor information generated by the central nervous system (CNS) plays a critical role in the activities of all animals. In this work, a novel, macroscopic and model-independent approach is presented for creating different patterns of coupled neural oscillations observed in biological central pattern generators (CPG) during the control of legged locomotion. Based on a simple distributed state machine, which consists of two nodes sharing pre-defined number of resources, the concept of oscillatory building blocks (OBBs) is summarised for the production of elaborated rhythmic patterns. Various types of OBBs can be designed to construct a motion joint of one degree-of-freedom (DOF) with adjustable oscillatory frequencies and duty cycles. An OBBs network can thus be potentially built to generate a full range of locomotion patterns of a legged animal with controlled transitions between different rhythmic patterns. It is shown that gait pattern transition can be achieved by simply changing a single parameter of an OBB module. Essentially this simple mechanism allows for the consolidation of a methodology for the construction of artificial CPG architectures behaving as an asymmetric Hopfield neural network. Moreover, the proposed CPG model introduced here is amenable to analogue and/or digital circuit integration.

KeywordsCentral pattern generator; Oscillatory building blocks; Legged locomotion; Parallel processing systems
PublisherSpringer
JournalNeural Computing and Applications
ISSN0941-0643
Electronic1433-3058
Publication dates
Online16 Mar 2016
Print30 Nov 2017
Publication process dates
Deposited08 Apr 2016
Accepted16 Feb 2016
Submitted23 Jul 2015
Output statusPublished
Accepted author manuscript
Copyright Statement

This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use https://www.springernature.com/gp/open-research/policies/accepted-ma... , but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s00521-016-2237-4

Digital Object Identifier (DOI)https://doi.org/10.1007/s00521-016-2237-4
Web of Science identifierWOS:000412313900035
LanguageEnglish
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