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Visual Perception and Reproduction for Imitative Learning of A Partner Robot

机译:视觉感知和复制,用于伙伴机器人的模仿学习

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摘要

This paper proposes visual perception and model reproduction based on imitation of a partner robot interacting with a human. First of all, we discuss the role of imitation, and propose the method for imitative behavior generation. After the robot searches for a human by using a CCD camera, human hand positions are extracted from a series of images taken from the CCD camera. Next, the position sequence of the extracted human hand is used as inputs to a fuzzy spiking neural network to recognize the position sequence as a motion pattern. The trajectory for the robot behavior is generated and updated by a steady-state genetic algorithm based on the human motions pattern. Furthermore, a self-organizing map is used for clustering human hand motion patterns. Finally, we show experimental results of imitative behavior generation through interaction with a human.
机译:本文提出了一种模仿伙伴机器人与人互动的视觉感知和模型再现方法。首先,我们讨论模仿的作用,并提出模仿行为的产生方法。在机器人使用CCD摄像机搜索人之后,从从CCD摄像机拍摄的一系列图像中提取人的手的位置。接下来,将提取的人手的位置序列用作模糊尖峰神经网络的输入,以将位置序列识别为运动模式。机器人行为的轨迹是通过基于人类运动模式的稳态遗传算法生成和更新的。此外,自组织图用于聚类人类手部运动模式。最后,我们展示了通过与人类互动产生模仿行为的实验结果。

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