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Designing an artificial attention system for social robots

机译:设计社交机器人的人工关注系统

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In this paper, we introduce the main components comprising the action-perception loop of an overarching framework implementing artificial attention, designed to fulfil the requirements of social interaction (i.e., reciprocity, and awareness), with strong inspiration on current theories in functional neuroscience. We demonstrate the potential of our framework, by showing how it exhibits coherent behaviour without any inbuilt prior expectations regarding the experimental scenario. Current research in cognitive systems for social robots has suggested that automatic attention mechanisms are essential to social interaction. In fact, we hypothesise that enabling artificial cognitive systems with middleware implementing these mechanisms will empower robots to perform adaptively and with a higher degree of autonomy in complex and social environments. However, this type of assumption is yet to be convincingly and systematically put to the test. The ultimate goal will be to test our working hypothesis and the role of attention in adaptive, social robotics.
机译:在本文中,我们介绍了主要组件,这些组件包括实现人为关注的总体框架的动作-感知循环,旨在满足社会互动的要求(即互惠和意识),并对功能神经科学的当前理论产生强烈启发。通过展示框架如何表现出连贯的行为,而又没有任何关于实验场景的内在事先期望,我们证明了框架的潜力。对社交机器人认知系统的最新研究表明,自动注意力机制对于社交互动至关重要。实际上,我们假设,通过具有实现这些机制的中间件的人工认知系统,将使机器人能够在复杂的社会环境中自适应地执行并具有更高的自治性。但是,这种假设尚未得到令人信服和系统地检验。最终目标将是检验我们的工作假设以及注意在自适应社交机器人中的作用。

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