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A Comparative Study among Three Automatic Gait Generation Methods for Quadruped Robots

机译:三足机器人三种自动步态生成方法的比较研究

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This paper introduces a comparison of three automatic gait generation methods for quadruped robots: GA (Genetic Algorithm), GP (genetic programming) and CPG (Central Pattern Generator). It aims to provide a useful guideline for the selection of gait generation methods. GA-based approaches seek to optimize paw locus in Cartesian space. GP-based techniques generate joint trajectories using regression polynomials. The CPGs are neural circuits that generate oscillatory output from an input coming from the brain. Optimizations for the three proposed methods are executed and analyzed using a Webots simulation of the quadruped robot built by Bioloid. The experimental comparisons and analyses provided herein will be an informative guidance for research of gait generation method.
机译:本文介绍了三次自动步态生成方法对四足机器人的比较:GA(遗传算法),GP(遗传编程)和CPG(中央图案发生器)。它旨在为选择步态生成方法提供有用的准则。基于GA的方法寻求优化笛卡尔空间中的爪子。基于GP的技术使用回归多项式产生关节轨迹。 CPG是神经电路,其产生来自来自大脑的输入的振荡输出。使用由Bioloid构建的四ruprupobot的展示来执行和分析三种提出的方​​法的优化。本文提供的实验比较和分析将是步态生成方法研究的信息指导。

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