论文标题
基于OpenStreetMap的LIDAR全球在城市环境中没有先前的LIDAR地图
OpenStreetMap-based LiDAR Global Localization in Urban Environment without a Prior LiDAR Map
论文作者
论文摘要
使用公开访问的地图，我们提出了一种新型的车辆定位方法，该方法可以在不使用事先检测和范围（LIDAR）地图的情况下应用。我们的方法通过定期计算OpenStreetMap位置的建筑物的距离来生成OSM描述符，并通过计算以常规角度计算从当前位置的建筑物点的最短距离来计算LIDAR描述符。比较OSM描述符和激光雷达描述符会产生高度准确的车辆定位。与使用先前的LiDAR图的方法相比，我们的方法提出了两个主要优点：（1）车辆定位不仅限于具有先前获得的LiDAR地图的位置，而且（2）我们的方法与基于LIDAR MAP的方法相当，尤其是在Kitti DataSet序列中最重要的一个候选者，尤其是优于其他方法。
Using publicly accessible maps, we propose a novel vehicle localization method that can be applied without using prior light detection and ranging (LiDAR) maps. Our method generates OSM descriptors by calculating the distances to buildings from a location in OpenStreetMap at a regular angle, and LiDAR descriptors by calculating the shortest distances to building points from the current location at a regular angle. Comparing the OSM descriptors and LiDAR descriptors yields a highly accurate vehicle localization result. Compared to methods that use prior LiDAR maps, our method presents two main advantages: (1) vehicle localization is not limited to only places with previously acquired LiDAR maps, and (2) our method is comparable to LiDAR map-based methods, and especially outperforms the other methods with respect to the top one candidate at KITTI dataset sequence 00.
