Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/14826

TitleHead motion stabilization during quadruped robot locomotion: combining CPGs and stochastic optimization methods
Author(s)Oliveira, Miguel
Santos, Cristina
Costa, L.
Rocha, Ana Maria A. C.
Ferreira, Manuel João Oliveira
KeywordsAutonomous robots
Bio-Inspired architecture
Constraint-handling techniques
CPGs,
Issue dateMar-2011
JournalInternational Journal of Natural Computing Research (ijncr)
Abstract(s)In this work, the authors propose a combined approach based on a controller architecture that is able to generate locomotion for a quadruped robot and a global optimization algorithm to generate head movement stabilization. The movement controllers are biologically inspired in the concept of Central Pattern Generators (CPGs) that are modelled based on nonlinear dynamical systems, coupled Hopf oscillators. This approach allows for explicitly specified parameters such as amplitude, offset and frequency of movement and to smoothly modulate the generated oscillations according to changes in these parameters. The overall idea is to generate head movement opposed to the one induced by locomotion, such that the head remains stabilized. Thus, in order to achieve this desired head movement, it is necessary to appropriately tune the CPG parameters. Three different global optimization algorithms search for this best set of parameters. In order to evaluate the resulting head movement, a fitness function based on the Euclidean norm is investigated. Moreover, a constraint-handling technique based on tournament selection was implemented.
TypeArticle
URIhttp://hdl.handle.net/1822/14826
Peer-Reviewedyes
AccessOpen access
Appears in Collections:DEI - Artigos em revistas internacionais

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