自主地面车辆三维点云分割

Danilo Habermann, A. Hata, D. Wolf, F. Osório
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引用次数: 9

摘要

在自主地面车辆和移动机器人领域,点云分割是提高障碍物检测和分类性能的重要步骤。本文研究和比较了三维激光传感器点云的分割方法的性能,更具体地说,是由Velodyne HDL32获得的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D Point Clouds Segmentation for Autonomous Ground Vehicle
Point clouds segmentation is an essential step to improve the performance of obstacle detection and classification in areas of autonomous ground vehicles and mobile robotics. This paper presents a study and comparison of the performance of segmentation methods using point clouds coming from a 3D laser sensor, more specifically obtained from a Velodyne HDL32.
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