Sensitivity analysis of a crawl gait multi-objective optimization system

Authors:
Miguel Oliveira;Pedro Silva;Cristina Santos;Lino Costa
Affiliations:
Algoritmi Center, School of Engineering, University of Minho, Guimarães, Portugal;Algoritmi Center, School of Engineering, University of Minho, Guimarães, Portugal;Algoritmi Center, School of Engineering, University of Minho, Guimarães, Portugal;Algoritmi Center, School of Engineering, University of Minho, Guimarães, Portugal
Venue:
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Year:
2013

Citing 2
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A fast and elitist multiobjective genetic algorithm: NSGA-II

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Abstract

This paper describes the analysis of a stable crawl gait multi-objective optimization system that combines bio-inspired Central Patterns Generators (CPGs) and a multi-objective evolutionary algorithm. In order to optimize the crawl gait, a multi-objective problem, an optimization system based on NSGA-II allows to find a set of non-dominated solutions that correspond to different motor solutions. The experimental results highlight the effectiveness of this multi-objective approach.