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Multi-Aspect Approach to Robotic Anticipation for Supporting Human's Multiple-Intelligence in Natural Scene

机译:用于支持人类多重情报的机器人预期的多方面方法

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A multi-aspect approach is applied to one-step anticipation for tightening human-robot interaction in naturally complex scene. Via symbolic massage exchange, human's linguistic intelligence identifies possible solutions by robotic intelligence. In reference to signal space as operable representation of the scene, human's body-kinesthetic intelligence and robotic control systems are co-oriented. As a common basis of these interaction aspects, in this paper, visible class of 'anticipants' is introduced on multi-viewpoint imagery. Despite not-yet-structured representation, the anticipants focalizes robotic intelligence to the scope of human's subsequent performances.
机译:一种多方面方法适用于用于收紧自然复杂场景中的人机机器人相互作用的一步预期。通过符号按摩交换,人类的语言智能通过机器人智能识别可能的解决方案。在参考现场可操作表示的信号空间,人体 - 运动智能和机器人控制系统是共同的。作为这些互动方面的常见基础,本文在多视点图像上引入了可见的“预期”。尽管尚未结构化的代表性,但预期会将机器人智能聚集到人类随后的表现的范围。

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