Adaptive dynamic control of quadrupedal robotic gaits with artificial reaction networks

Claire E. Gerrard*, John McCall, George M. Coghill, Christopher Macleod

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The Artificial Reaction Network (ARN) is a bio-inspired connectionist paradigm based on the emerging field of Cellular Intelligence. It has properties in common with both AI and Systems Biology techniques including Artificial Neural Networks, Petri Nets, and S-Systems. In this paper, elements of temporal dynamics and pattern recognition are combined within a single ARN control system for a quadrupedal robot. The results show that the ARN has similar applicability to Artificial Neural Network models in robotic control tasks. In comparison to neural Central Pattern Generator models, the ARN can control gaits and offer reduced complexity. Furthermore, the results show that like spiky neural models, the ARN can combine pattern recognition and complex temporal control functionality in a single network.

Original languageEnglish
Title of host publicationNeural Information Processing - 19th International Conference, ICONIP 2012, Proceedings
Pages280-287
Number of pages8
EditionPART 1
DOIs
Publication statusPublished - 19 Nov 2012
Event19th International Conference on Neural Information Processing, ICONIP 2012 - Doha, Qatar
Duration: 12 Nov 201215 Nov 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7663 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Neural Information Processing, ICONIP 2012
CountryQatar
CityDoha
Period12/11/1215/11/12

Keywords

  • Artificial Neural Networks
  • Artificial Reaction Networks
  • Biochemical Networks
  • Cellular Intelligence

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Gerrard, C. E., McCall, J., Coghill, G. M., & Macleod, C. (2012). Adaptive dynamic control of quadrupedal robotic gaits with artificial reaction networks. In Neural Information Processing - 19th International Conference, ICONIP 2012, Proceedings (PART 1 ed., pp. 280-287). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7663 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-34475-6_34