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

Research output: Book chapterChapterpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Science and Business Media Deutschland GmbH
Pages141-155
Number of pages15
DOIs
Publication statusPublished - 2024

Publication series

NameStudies in Computational Intelligence
Volume1146
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

Keywords

  • Central pattern generator
  • Evolutionary algorithm
  • Nengo
  • Spiking neural network

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