首页> 外文期刊>International Journal of Artificial Intelligence Tools: Architectures, Languages, Algorithms >USING KNOWLEDGE REPRESENTATION FOR PERCEPTUAL ANCHORING IN A ROBOTIC SYSTEM
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USING KNOWLEDGE REPRESENTATION FOR PERCEPTUAL ANCHORING IN A ROBOTIC SYSTEM

机译:在机器人系统中使用知识表示法进行感知锚定

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In this work we introduce symbolic knowledge representation and reasoning capabilities to enrich perceptual anchoring. The idea that encompasses perceptual anchoring is the creation and maintenance of a connection between the symbolic and perceptual description that refer to the same object in the environment. In this work we further extend the symbolic layer by combining a knowledge representation and reasoning (KRR) system with the anchoring module to exploit a knowledge inference mechanisms. We implemented a prototype of this novel approach to explore through initial experimentation the advantages of integrating a symbolic knowledge system to the anchoring framework in the context of an intelligent home. Our results show that using the KRR we are better able to cope with ambiguities in the anchoring module through exploitation of human robot interaction.
机译:在这项工作中,我们介绍了符号知识表示和推理功能,以丰富感性锚定。包含感知锚定的想法是在引用环境中相同对象的符号描述和感知描述之间创建和维护连接。在这项工作中,我们通过将知识表示和推理(KRR)系统与锚定模块相结合来进一步扩展符号层,以利用知识推理机制。我们实施了这种新颖方法的原型,以通过初始实验探索在智能家居环境中将符号知识系统集成到锚定框架中的优势。我们的结果表明,使用KRR,我们可以更好地通过利用人机交互来解决锚定模块中的歧义。

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