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Triangulation Hough Transform Based Fusion of Sonar Data for Mobile Robotics

机译:基于三角测量和Hough变换移动机器人声纳数据的融合

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Polaroid sonar sensors are still one of the most widely used sensors in mobile robotics. In this paper a novel sensor fusion scheme called THF (Triangulation Hough Fusion), which combines the advantages of TBF (Triangulation Based Fusion) and CIHT (Cluster Inhibiting Hough Transform), is presented. The idea of THF lies in that a modified Hough transform is employed on the points extracted by TBF, not on the raw sonar data directly. THF algorithm applied on clustered and noisy sonar data could reliably detect both point and line segment features of the environment. We demonstrate the effectivity of THF algorithm by extracting geometric features in a simulated indoor environment, in which a mobile robot travels with pedestrians moving around casually. Experiments demonstrate that THF is an effective and efficient scheme for detecting both point features and line segment features, especially in the structured environment.
机译:宝丽来声驶传感器仍然是移动机器人中最广泛使用的传感器之一。本文在介绍了一种新的传感器融合方案,称为THF(三角测量霍夫融合),它结合了TBF(基于三角型融合)和CIHT(抑制霍夫变换)的优点。 THF的想法在于,在TBF提取的点上采用修改的Hough变换,而不是直接原始声纳数据。在聚类和嘈杂的声纳数据上应用的THF算法可以可靠地检测环境的两个点和线段特征。我们通过提取模拟室内环境中的几何特征来证明THF算法的有效性,其中移动机器人随随便移动的行人行驶。实验表明,THF是一种有效且有效的方案,用于检测点特征和线段特征,尤其是在结构化环境中。

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