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Applied Computational Intelligence and Soft Computing
Volume 2010, Article ID 413179, 12 pages
Review Article

A Review of Gait Optimization Based on Evolutionary Computation

School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China

Received 1 September 2009; Revised 21 March 2010; Accepted 22 April 2010

Academic Editor: Oliver Kramer

Copyright © 2010 Daoxiong Gong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Gait generation is very important as it directly affects the quality of locomotion of legged robots. As this is an optimization problem with constraints, it readily lends itself to Evolutionary Computation methods and solutions. This paper reviews the techniques used in evolution-based gait optimization, including why Evolutionary Computation techniques should be used, how fitness functions should be composed, and the selection of genetic operators and control parameters. This paper also addresses further possible improvements in the efficiency and quality of evolutionary gait optimization, some problems that have not yet been resolved and the perspectives for related future research.