基于婴儿运动牙牙学语的机器人伸手的神经元模型
Neurally Plausible Model of Robot Reaching Inspired by Infant Motor Babbling
摘要：
在本文中，我们提出了一个神经合理的模型，机器人达到人类婴儿达到的启发，是基于体现人工智能，强调的重要性，一个代理和世界的感觉运动的相互作用。该模型包括通过运动牙牙学语学习感觉-运动相关性以及使用扩散激活的手臂运动规划。该模型由三层神经映射组成，具有代表相同感觉运动空间的并行结构。运动咿呀学语阶段塑造了三个神经地图的结构以及它们内部和之间的连接。我们描述了这个模型的实施和调查，这个实施使用一个简单的达成任务的人形机器人。机器人已经成功地学会了从测试集规划达到运动具有高精度和平滑度。
英文摘要：
In this paper we present a neurally plausible model of robot reaching inspired by human infant reaching that is based on embodied artificial intelligence, which emphasizes the importance of the sensory-motor interaction of an agent and the world. This model encompasses both learning sensory-motor correlations through motor babbling and also arm motion planning using spreading activation. This model is organized in three layers of neural maps with parallel structures representing the same sensory-motor space. The motor babbling period shapes the structure of the three neural maps as well as the connections within and between them. We describe an implementation of this model and an investigation of this implementation using a simple reaching task on a humanoid robot. The robot has learned successfully to plan reaching motions from a test set with high accuracy and smoothness.
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