Genetic programming based automatic gait generation for quadruped robots

Authors:
Kisung Seo;Soohwan Hyun
Affiliations:
Seokyeong University, Seoul, South Korea;Seokyeong University, Seoul, South Korea
Venue:
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Year:
2008

Citing 1
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A review of gait optimization based on evolutionary computation

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A comparative study between genetic algorithm and genetic programming based gait generation methods for quadruped robots

EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Co-evolutionary approach to design of robotic gait

EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation

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Abstract

This paper introduces a new approach to develop fast gait for quadruped robot using genetic programming (GP). Several recent approaches have focused on using genetic algorithm (GA) to generate gait automatically and shown significant improvements over previous results. Most of current GA based approaches use pre-selected parameters, but it is difficult to select the appropriate parameters for the optimization of gait. To overcome these problems of GA based approach, we proposed an efficient approach which optimizes joint angle trajectories using genetic programming. Our GP based method has obtained much better results than GA based approaches for experiments of Sony AIBO ers-7 in Webots environment. The elite archive mechanism(EAM) was introduced to prevent premature convergence problems in GP and has shown improvements.