Evolutionary Deployment of Central Pattern Generators for Legged Robots Using Nengo

Ricardo Pérez-López, Andrés Espinal, Marco Sotelo-Figueroa, Erick I. Guerra-Hernandez, Patricia Batres-Mendoza, Horacio Rostro-Gonzalez

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Resumen

In this paper, we present an evolutionary design methodology of Central Pattern Generator (CPG)-based locomotion systems for hexapod and quadrupedal robots. The CPGs are built as Spiking Neural Networks, whose synaptic connections and weights are directly configured by an evolutionary algorithm in order that CPGs generate rhythmic and periodical signals to carry out robotic locomotion. The CPGs are fully designed and implemented using Nengo simulator. There were obtained CPGs for different locomotion patterns for both, hexapod and quadruped robots. The obtained CPGs achieve behaviours reported in the state of the art with smaller architectures.

Idioma originalInglés
Título de la publicación alojadaStudies in Computational Intelligence
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas141-155
Número de páginas15
DOI
EstadoPublicada - 2024

Serie de la publicación

NombreStudies in Computational Intelligence
Volumen1146
ISSN (versión impresa)1860-949X
ISSN (versión digital)1860-9503

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