Intelligent approaches in locomotion

Jonathan Wright, Ivan Jordanov*

*Corresponding author for this work

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

Abstract

In this paper we review more than 50 publications and try to not only give a snap shot of the current state of the art research in the area, but also to critically analyse and compare different methodologies used in this research field. Among the investigated intelligent approaches for solving locomotion problems are Neural Networks, Hidden Markov models, Rule Based and Fuzzy Logic systems, as well as Analytical concepts. We try to compare those methods based on the quality of the produced solutions in terms of time, stability, correctness and the expense and cost for achieving them. At the end of each section we list the advantages and disadvantages of the reviewed methods and scrutinise them considering the complexity of the approaches, their applicability to the investigated locomotion tasks and the constraints of the produced solutions.

Original languageEnglish
Title of host publication2012 International Joint Conference on Neural Networks, IJCNN 2012
PublisherIEEE
Number of pages8
ISBN (Electronic)9781467314909, 9781467314893
ISBN (Print)9781467314886
DOIs
Publication statusPublished - 30 Jul 2012
Event2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 - Brisbane, QLD, Australia
Duration: 10 Jun 201215 Jun 2012

Publication series

NameProceedings of the International Joint Conference on Neural Networks
PublisherIEEE
ISSN (Print)2161-4393
ISSN (Electronic)2161-4407

Conference

Conference2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012
Country/TerritoryAustralia
CityBrisbane, QLD
Period10/06/1215/06/12

Keywords

  • central pattern generator
  • fuzzy logic
  • hidden Markov models
  • Legged locomotion
  • neural networks
  • optimisation

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