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Genetic Algorithm for Walking Robots Motion Optimization

机译:行走机器人运动优化的遗传算法

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The paper presents a method to determine the optimal solution regarding the movement done by the leg of a hexapod walking robot with three degrees of freedom, with higher positioning precision taking into account the importance of three factors (Precision, Movement and Friction). To find the coefficients that establish the order of these factors we use an Analytical Hierarchy Process. With these coefficients we build the fitness function for a genetic algorithm that is slightly modified (instead of two chromosomes crossed, we crossed three) in order to obtain a diversity in the exchanged information. The obtained results prove that, applying the genetic algorithm in correlation with the analytic hierarchy method of processing, we can optimize the precision in the robot movement with a relative small increase of the consumed energy.
机译:本文介绍了一种确定关于六角形行走机器人腿部采用三度自由度完成的运动的最佳解决方案,考虑到三种因素的重要性(精确,运动和摩擦)。要找到建立这些因素顺序的系数,我们使用分析层次结构。对于这些系数,我们构建遗传算法的健身功能,该遗传算法略微修改(而不是交叉的两个染色体,我们跨过三个),以便在交换信息中获得分集。所获得的结果证明,应用遗传算法与分析层次的处理方法相关,我们可以优化机器人运动中的精度,相对较小的消耗能量。

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