基于神经网络的仿人机器人手部姿态控制

2014 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA) Pub Date : 2014-05-05 DOI:10.1109/CIVEMSA.2014.6841450

E. Huluta, Ricardo Freire da Silva, T. E. D. Oliveira

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引用次数: 3

摘要

提出了一种基于神经网络的多指机械手控制方法。由于构建和控制其3D运动的复杂性，研究人员在试图生产类似人类的可训练机器人手时面临着一些挑战。本文的作者通过开发一个框架提供了一个改进的解决方案，该框架可以通过使用人工神经网络轻松训练和控制机械手。

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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Neural network-Based hand posture control of a humanoid Robot Hand

This paper presents a novel method to provide Neural Network Based Control of a Multi-finger Robot Hand. There are several challenges known from the literature that researchers are facing when they are trying to produce a human-like trainable robotic hand due to the complexity of building it and controlling its 3D movement. The authors of this article are providing an improved solution to this problem by developing a framework that enables easy training and control of a Robotic Hand by using Artificial Neural Networks.

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2014 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)

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