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A LIDAR SLAM Based on Point-Line Features for Underground Mining Vehicle

机译:基于点线特征的地下采矿车激光雷达

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This paper presents an original 2D LIDAR SLAM based on point and line features to the underground tunnel environment. In our algorithm, the point features are extracted by using Curvature detector with range information weights. The line features detection algorithm contains segmentation by two hierarchical levels and line fitting. We present the approach used in our prototype of underground mining truck which achieves real-time localization and mapping at a 5cm resolution. We provide experimental results and comparisons to other approaches. The results show that this proposed method has good robustness and accuracy.
机译:本文针对地下隧道环境,提出了一种基于点和线特征的原始2D LIDAR SLAM。在我们的算法中,使用具有范围信息权重的曲率检测器提取点特征。线特征检测算法包含按两个层次级别进行的分割和线拟合。我们介绍了地下矿用卡车原型中使用的方法,该方法可实现5cm分辨率的实时定位和地图绘制。我们提供实验结果并与其他方法进行比较。结果表明,该方法具有良好的鲁棒性和准确性。

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