Dynamic and interactive generation of object handling behaviors by a small humanoid robot using a dynamic neural network model
Dynamic and interactive generation of object handling behaviors by a small humanoid robot using a dynamic neural network model
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DOI：
10.1016/j.neunet.2006.02.007
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发表时间：
2006-04-01
期刊：
影响因子：
7.8
通讯作者：
Tani, Jun
中科院分区：
文献类型：
--
作者：
Ito, Masato;Noda, Kuniaki;Tani, Jun
本研究提出了一个小型人形机器人使用动态神经网络模型，参数偏差的递归神经网络（RNNPB）的对象处理行为的学习实验。第一个实验表明，机器人学习不同类型的球处理行为，使用人类直接教学后，机器人能够产生足够的球处理电机序列位于机器人的手和球之间的相对位置。同样的方案被应用到块处理学习任务，它表明，机器人可以在学习不同的块处理序列之间切换，位于人类支持者的交互方式。我们的分析表明，夹带的RNNPB的内部存储器结构，通过对象和人类的支持者的相互作用是必不可少的机制，为那些观察到的机器人的行为（c）2006爱思唯尔有限公司保留所有权利。
This study presents experiments on the learning of object handling behaviors by a small humanoid robot using a dynamic neural network model, the recurrent neural network with parametric bias (RNNPB). The first experiment showed that after the robot learned different types of ball handling behaviors using human direct teaching, the robot was able to generate adequate ball handling motor sequences situated to the relative position between the robot's hands and the ball. The same scheme was applied to a block handling learning task where it was shown that the robot can switch among learned different block handling sequences, situated to the ways of interaction by human supporters. Our analysis showed that entrainment of the internal memory structures of the RNNPB through the interactions of the objects and the human supporters are the essential mechanisms for those observed situated behaviors of the robot (c) 2006 Elsevier Ltd. All rights reserved.