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Natural landmark extraction for mobile robot navigation based on an adaptive curvature estimation

机译:基于自适应曲率估计的移动机器人导航自然地标提取

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摘要

This paper proposes a geometrical feature detection system which is to be used with conventional 2D laser range finders. It consists of three main modules: data acquisition and pre-processing, segmentation and landmark extraction and characterisation. The novelty of this system is a new approach for laser data segmentation based on an adaptive curvature estimation. Contrary to other works, this approach divides the laser scan into line and curve segments. Then, these items are used to directly extract several types of landmarks associated with real and virtual features of the environment (corners, center of tree-like objects, line segments and edges). For each landmark, characterisation provides not only the parameter vector, but also complete statistical information, suitable to be used in a localization and mapping algorithm. Experimental results show that the proposed approach is efficient to detect landmarks for structured and semi-structured environments.
机译:本文提出了一种几何特征检测系统,该系统将与常规2D激光测距仪一起使用。它由三个主要模块组成:数据采集和预处理,分割以及界标提取和表征。该系统的新颖性是一种基于自适应曲率估计的激光数据分割新方法。与其他工作相反,此方法将激光扫描分为线段和曲线段。然后,这些项目用于直接提取与环境的真实和虚拟特征(角,树状对象的中心,线段和边缘)关联的几种类型的地标。对于每个界标,特征化不仅提供参数矢量,而且还提供完整的统计信息,适合在定位和映射算法中使用。实验结果表明,该方法可有效检测结构化和半结构化环境中的界标。

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