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Reasoning about shadows in a mobile robot environment

机译:关于移动机器人环境中阴影的推理

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摘要

This paper describes a logic-based formalism for qualitative spatial reasoning with cast shadows (Perceptual Qualitative Relations on Shadows, or PQRS) and presents results of a mobile robot qualitative self-localisation experiment using this formalism. Shadow detection was accomplished by mapping the images from the robot's monocular colour camera into a HSV colour space and then thresholding on the V dimension. We present results of self-localisation using two methods for obtaining the threshold automatically: in one method the images are segmented according to their grey-scale histograms, in the other, the threshold is set according to a prediction about the robot's location, based upon a qualitative spatial reasoning theory about shadows. This theory-driven threshold search and the qualitative self-localisation procedure are the main contributions of the present research. To the best of our knowledge this is the first work that uses qualitative spatial representations both to perform robot self-localisation and to calibrate a robot's interpretation of its perceptual input.
机译:本文介绍了一种基于逻辑的形式主义,用于使用投射阴影进行定性空间推理(阴影上的感知定性关系,或PQRS),并提出了使用此形式主义进行的移动机器人定性自定位实验的结果。阴影检测是通过将来自机器人的单眼彩色摄像机的图像映射到HSV颜色空间中,然后在V维度上进行阈值化来完成的。我们介绍了使用两种自动获取阈值的方法进行自我定位的结果:一种方法是根据图像的灰度直方图对图像进行分割,另一种方法是根据对机器人位置的预测来设置阈值关于阴影的定性空间推理理论。这种理论驱动的阈值搜索和定性的自定位过程是本研究的主要贡献。据我们所知,这是第一项使用定性空间表示来执行机器人的自动定位和校准机器人对其感知输入的解释的工作。

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