Structured learning of a partner robot based on perceiving-acting cycle
Structured learning of a partner robot based on perceiving-acting cycle
复制标题
基于感知-动作循环的伙伴机器人结构化学习
DOI：
10.1109/cira.2003.1222103
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
D. Hisajima
中科院分区：
文献类型：
--
作者：
N. Kubota;D. Hisajima
本文提出了一种从心理学的角度来构建伙伴机器人和人类之间的相互关系的学习方法。首先，感知-动作循环的概念被应用于学习伙伴机器人的感知和动作之间的关系。此外，模块化神经网络用于通过与人的交互来指定和学习动作分割。在本文中，我们专注于视觉系统感知的合作伙伴机器人。准备一个永久模块，用于根据当前状态提取特定的感知信息。实验结果表明，在伙伴机器人与人之间的交流过程中，可以进行交互式学习。
This paper proposes a learning method for constructing the interrelation between a partner robot and human from the psychological point of view. First, the concept of perceiving-acting cycle is applied for learning the relationship between perception and action of a partner robot. Furthermore, modular neural networks are used for specifying and learning action segmentations through the interaction with a human. In this paper, we focus on the visual system for perception of the partner robot. A perpetual module is prepared for extracting specific perceptual information according to the current state. Some experimental results show the interactive learning can be done in the communication process between a partner robot and a human.