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COOPERATIVE KNOWLEDGE BASED PERCEPTUAL ANCHORING

机译:基于合作知识的知觉锚定

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摘要

In settings where heterogenous robotic systems interact with humans, information from the environment must be systematically captured, organized and maintained in time. In this work, we propose a model for connecting perceptual information to semantic information in a multi-agent setting. In particular, we present semantic cooperative perceptual anchoring, that captures collectively acquired perceptual information and connects it to semantically expressed commonsense knowledge. We describe how we implemented the proposed model in a smart environment, using different modern perceptual and knowledge representation techniques. We present the results of the system and investigate different scenarios in which we use the commonsense together with perceptual knowledge, for communication, reasoning and exchange of information.
机译:在异构机器人系统与人类互动的环境中,必须及时捕获,组织和维护来自环境的信息。在这项工作中,我们提出了一种在多主体设置中将感知信息连接到语义信息的模型。特别是,我们提出了语义协作感知锚定,它捕获了集体获取的感知信息并将其连接到语义表达的常识知识。我们描述了我们如何使用不同的现代感知和知识表示技术在智能环境中实现建议的模型。我们介绍系统的结果,并研究将常识与感知知识一起用于交流,推理和信息交换的不同场景。

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