论文标题
学习使用激光强度图本地化
Learning to Localize Using a LiDAR Intensity Map
论文作者
论文摘要
在本文中，我们提出了一种用于自动驾驶汽车的实时，校准敏捷和有效的定位系统。我们的方法学会了将在线LIDAR扫描和强度图嵌入到联合深层嵌入空间中。然后，通过嵌入之间的有效卷积匹配来进行定位。我们的完整系统可以在15Hz实时运行，同时在不同的激光雷达传感器和环境中实现厘米水平的准确性。我们的实验说明了在大规模数据集中提出的方法的性能，该数据集由超过4000公里的驾驶组成。
In this paper we propose a real-time, calibration-agnostic and effective localization system for self-driving cars. Our method learns to embed the online LiDAR sweeps and intensity map into a joint deep embedding space. Localization is then conducted through an efficient convolutional matching between the embeddings. Our full system can operate in real-time at 15Hz while achieving centimeter level accuracy across different LiDAR sensors and environments. Our experiments illustrate the performance of the proposed approach over a large-scale dataset consisting of over 4000km of driving.
