Robot behavior evolution using knowledge array network

Masakazu Suzuki
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引用次数: 2

Abstract

In this article proposed is a method of robot behavior evolution using a knowledge array network. The knowledge array network is formed by organically connecting knowledge arrays which are used in the Intelligent Composite Motion Control (ICMC) to store and utilize the empirical knowledge and adapt to inexperienced situations. The ICMC is a methodology to build up robot systems in which robots can realize complex and dexterous behaviors autonomously and adaptively based upon parameter optimization and utilization of empirical knowledge only if the motion control for fundamental element motions is given. After reviewing the ICMC and the array operations, presented is the framework of behavior evolution. It is shown how the behavior evolution from primitive motions to complicated tasks is realized, that is, it is shown how the dexterous ball throwing with robotic manipulator, for example, is coordinated from simple joint rotations.
基于知识阵列网络的机器人行为演化
本文提出了一种基于知识阵列网络的机器人行为进化方法。知识阵列网络是将智能复合运动控制(ICMC)中使用的知识阵列有机地连接起来,以存储和利用经验知识并适应经验情况。ICMC是在给定基本单元运动控制的前提下,通过参数优化和利用经验知识,构建机器人系统,使机器人能够自主、自适应地实现复杂灵巧行为的一种方法。在回顾了ICMC和数组操作之后,提出了行为演化的框架。展示了如何实现从原始运动到复杂任务的行为进化,即如何从简单的关节旋转协调以机械臂灵巧投球为例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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