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An Obstacle Classification Method Using Multi-feature Comparison Based on 2D LIDAR Database

机译:基于2D LIDAR数据库的多特征比较的障碍分类方法

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We propose an obstacle classification method using multi feature comparison based on 2D LIDAR. The existing obstacle classification method based on 2D LIDAR has an advantage in terms of accuracy and shorter calculation time. However, it was difficult to classify obstacle type, and therefore accurate path planning was not possible. To overcome this problem, a method of classifying obstacle type based on width data had been proposed. However, width data was not sufficient to enable accurate obstacle classification. The proposed algorithm of this paper involves comparison with database to classify obstacle type. Database was generated using width, intensity and range variance data. Experiments using a real autonomous vehicle in a real environment showed that calculation time decreased in comparison with 3D LIDAR-based method, thus demonstrating the possibility of obstacle type classification using single 2D LIDAR.
机译:我们提出了一种基于2D LIDAR的多特征比较的障碍分类方法。基于2D LIDAR的现有障碍分类方法在准确性和更短的计算时间方面具有优势。但是,很难分类障碍物类型,因此无法准确的路径规划。为了克服这个问题,提出了一种基于宽度数据对障碍物类型进行分类的方法。但是,宽度数据不足以实现准确的障碍分类。本文所提出的算法涉及与数据库进行对分类障碍物类型的比较。使用宽度,强度和范围方差数据生成数据库。在真实环境中使用真正自主车辆的实验表明,与基于3D激光雷达的方法相比,计算时间降低,从而展示了使用单个2D激光雷达障碍型分类的可能性。

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