论文标题
使用正常分布转换多个3D激光雷达的表征和映射
Characterization of Multiple 3D LiDARs for Localization and Mapping using Normal Distributions Transform
论文作者
论文摘要
在这项工作中，我们介绍了十个不同的3D激光雷达传感器的详细比较，涵盖了制造商，型号和激光配置，用于映射和车辆本地化的任务，作为常见参考，正常分布变换（NDT）算法在自动驾驶的自动驾驶开源开源平台AutoWare中实现。本研究中使用的激光雷达数据是我们的LIDAR基准测试和参考（LIBRE）数据集的一个子集，该数据集是从每个传感器中独立捕获的。在这项研究中，我们分析了（1）3D映射的任务，包括基于平均地图熵的评估图质量，以及（2）使用地面真实参考图。
In this work, we present a detailed comparison of ten different 3D LiDAR sensors, covering a range of manufacturers, models, and laser configurations, for the tasks of mapping and vehicle localization, using as common reference the Normal Distributions Transform (NDT) algorithm implemented in the self-driving open source platform Autoware. LiDAR data used in this study is a subset of our LiDAR Benchmarking and Reference (LIBRE) dataset, captured independently from each sensor, from a vehicle driven on public urban roads multiple times, at different times of the day. In this study, we analyze the performance and characteristics of each LiDAR for the tasks of (1) 3D mapping including an assessment map quality based on mean map entropy, and (2) 6-DOF localization using a ground truth reference map.
