论文标题
尽管交通有挑战性阻塞，但激光雷达横向定位
LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic
论文作者
论文摘要
本文介绍了一种用于改善激光雷达侧面定位系统鲁棒性的系统。通过包括对传感器看不见的道路边界的检测（由于遮挡，例如交通），可以实现这一目标，但可以通过我们闭合的道路边界推理深神经网络位置。我们展示了一个示例应用程序，其中使用相机流的融合来初始化横向定位。我们展示了超过四次通过牛津中部的驱动力 - 总计40公里的驾驶 - 绩效的增长，推断出封闭的道路边界带来的推动。
This paper presents a system for improving the robustness of LiDAR lateral localisation systems. This is made possible by including detections of road boundaries which are invisible to the sensor (due to occlusion, e.g. traffic) but can be located by our Occluded Road Boundary Inference Deep Neural Network. We show an example application in which fusion of a camera stream is used to initialise the lateral localisation. We demonstrate over four driven forays through central Oxford - totalling 40 km of driving - a gain in performance that inferring of occluded road boundaries brings.
