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Optimization of a Robotics Gaze Control System

机译:机器人凝视控制系统的优化

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Gaze control is an important issue in the interaction between a robot and humans. In particular, the decision of who to pay attention to in a multi-party conversation is a way of improving a robot's naturalness in human-robot interaction. A system based on a competitive neural network can decide who to look at with a smooth transition in the focus of attention when significant changes in stimuli are produced. One important aspect in this process is the configuration of the different parameters of such a neural network. The weights of the different stimuli have to be computed in order to achieve behavior similar to humans. This article explains how these weights can be obtained by solving an optimization problem. The experiments carried out and some results are also presented.
机译:凝视控制是机器人与人类之间的相互作用的重要问题。 特别是,在多党对话中遵守谁的决定是一种改善机器人在人机互动中的自然的一种方式。 基于竞争性神经网络的系统可以在产生刺激的重大变化时,决定谁在关注的焦点中进行平滑过渡。 该过程中的一个重要方面是这种神经网络的不同参数的配置。 必须计算不同刺激的权重,以便实现类似于人类的行为。 本文介绍了如何通过解决优化问题来获得这些权重。 还介绍了进行的实验和一些结果。

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