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

机译:基于二维LIDAR数据库的多特征比较障碍物分类方法

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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物分类方法。现有的基于2D LIDAR的障碍物分类方法在准确性和缩短计算时间方面具有优势。但是,很难对障碍物类型进行分类,因此无法进行准确的路径规划。为了克服这个问题,已经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物分类。本文提出的算法包括与数据库进行比较以对障碍物类型进行分类。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实自动驾驶汽车进行的实验表明,与基于3D LIDAR的方法相比,计算时间有所减少,从而证明了使用单个2D LIDAR进行障碍物类型分类的可能性。

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