A successive learning neuro control system shooting irregular moving object

Proceedings of 1993 2nd IEEE International Workshop on Robot and Human Communication Pub Date : 1993-11-03 DOI:10.1109/ROMAN.1993.367699

K. Hirota, T. Tsurumaru, A. Motegi, M. Ohtani, N. Yubazaki, T. Miyajima

引用次数: 0

Abstract

A successive learning control system based on a neural network technique with a genetic algorithm has been developed to simulate a human real-time learning process. As an application experiment, a 3 degree-of-freedom arm robot shoots a ball equipped with a CCD camera at an irregular moving basket. Where the hitting rate is improved by the successive learning control and the final value was 23% in average, 40% in maximum.<>

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一种射击不规则运动物体的连续学习神经控制系统

为了模拟人的实时学习过程，提出了一种基于遗传算法的神经网络连续学习控制系统。作为一项应用实验，一个3自由度的手臂机器人在一个不规则移动的篮筐上发射一个装有CCD相机的球。其中，连续学习控制提高了命中率，最终命中率平均为23%，最大值为40%。

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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Proceedings of 1993 2nd IEEE International Workshop on Robot and Human Communication

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