research-article

A CPG system based on spiking neurons for hexapod robot locomotion

Authors:

H. Rostro-Gonzalez,

P.A. Cerna-Garcia,

G. Trejo-Caballero,

C.H. Garcia-Capulin,

M.A. Ibarra-Manzano,

J.G. Avina-Cervantes,

C. Torres-HuitzilAuthors Info & Claims

Neurocomputing, Volume 170, Issue C

Pages 47 - 54

https://doi.org/10.1016/j.neucom.2015.03.090

Published: 25 December 2015 Publication History

Abstract

In this paper, we propose a locomotion system based on a central pattern generator (CPG) for a hexapod robot, suitable for embedded hardware implementation. The CPG system was built as a network of spiking neurons, which produce rhythmic signals for three different gaits (walk, jogging and run) in the hexapod robot. The spiking neuron model used in this work is a simplified form of the well-known generalized Integrate-and-Fire neuron model, which can be trained using the Simplex method. The use of spiking neurons makes the system highly suitable for digital hardware implementations that exploit the inherent parallelism to replicate the intrinsic, computationally efficient, distributed control mechanism of CPGs. The system has been implemented on a Spartan 6 FPGA board and fully validated on a hexapod robot. Experimental results show the effectiveness of the proposed approach, based on existing models and techniques, for hexapod rhythmic locomotion.

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Cited By

Çatalbaş BMorgül Ö(2022)Two-Legged Robot Motion Control With Recurrent Neural NetworksJournal of Intelligent and Robotic Systems10.1007/s10846-021-01553-5104:4Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1007/s10846-021-01553-5
Polykretis ITang GMichmizos K(2020)An Astrocyte-Modulated Neuromorphic Central Pattern Generator for Hexapod Robot Locomotion on Intel’s LoihiInternational Conference on Neuromorphic Systems 202010.1145/3407197.3407205(1-9)Online publication date: 28-Jul-2020
https://dl.acm.org/doi/10.1145/3407197.3407205
Korkmaz NKılıç R(2019)An Alternative Approach for Setting the Optimum Coupling Parameters Among the Neural Central Pattern Generators Considering the Amplitude and the Phase Error CalculationsNeural Processing Letters10.1007/s11063-019-10070-450:1(645-667)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s11063-019-10070-4
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Index Terms

A CPG system based on spiking neurons for hexapod robot locomotion
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks

Index terms have been assigned to the content through auto-classification.

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cover image Neurocomputing

Neurocomputing Volume 170, Issue C

December 2015

466 pages

ISSN:0925-2312

Issue’s Table of Contents

Copyright © Elsevier B.V.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 25 December 2015

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Cited By

Çatalbaş BMorgül Ö(2022)Two-Legged Robot Motion Control With Recurrent Neural NetworksJournal of Intelligent and Robotic Systems10.1007/s10846-021-01553-5104:4Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1007/s10846-021-01553-5
Polykretis ITang GMichmizos K(2020)An Astrocyte-Modulated Neuromorphic Central Pattern Generator for Hexapod Robot Locomotion on Intel’s LoihiInternational Conference on Neuromorphic Systems 202010.1145/3407197.3407205(1-9)Online publication date: 28-Jul-2020
https://dl.acm.org/doi/10.1145/3407197.3407205
Korkmaz NKılıç R(2019)An Alternative Approach for Setting the Optimum Coupling Parameters Among the Neural Central Pattern Generators Considering the Amplitude and the Phase Error CalculationsNeural Processing Letters10.1007/s11063-019-10070-450:1(645-667)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s11063-019-10070-4
Manzoor SCho YChoi Y(2019)Neural Oscillator Based CPG for Various Rhythmic Motions of Modular Snake Robot with Active JointsJournal of Intelligent and Robotic Systems10.1007/s10846-018-0864-y94:3-4(641-654)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s10846-018-0864-y
Chang QMei F(2018)A Bioinspired Gait Transition Model for a Hexapod RobotJournal of Robotics10.1155/2018/29136362018Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1155/2018/2913636
Chen QWang JYang SQin YDeng BWei X(2017)A real-time FPGA implementation of a biologically inspired central pattern generator networkNeurocomputing10.1016/j.neucom.2017.03.028244:C(63-80)Online publication date: 28-Jun-2017
https://dl.acm.org/doi/10.1016/j.neucom.2017.03.028
Zhang MQu HXie XKurths J(2017)Supervised learning in spiking neural networks with noise-thresholdNeurocomputing10.1016/j.neucom.2016.09.044219:C(333-349)Online publication date: 5-Jan-2017
https://dl.acm.org/doi/10.1016/j.neucom.2016.09.044
Shi RZhang XTian YDong SYao Y(undefined)A CPG-based control method for the rolling locomotion of a desert spider2016 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO)10.1109/ARSO.2016.7736289(243-248)
https://dl.acm.org/doi/10.1109/ARSO.2016.7736289

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