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Genetic programming based automatic gait generation for quadruped robots

Kisung Seo, Soohwan Hyun

Year
2008
Citations
11

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.

Keywords

GaitGenetic programmingComputer scienceGenetic algorithmRobotConvergence (economics)Artificial intelligenceSimulationMachine learning

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