论文标题
环顾四周：基于序列的雷达位置识别，并具有学习的旋转不变性
Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance
论文作者
论文摘要
本文详细介绍了一种应用程序，该应用可以通过频率调制的连续波雷达（这是一个有前途的传感器，可在移动自主权中开发），从而对位置识别的熟练程度进行了重大改进。我们展示了如何将用于雷达扫描的旋转不变的度量嵌入到基于序列的轨迹匹配系统中，通常应用于视觉传感器拍摄的视频。由于雷达扫描形成过程固有的完整水平视野，我们展示了如何操纵这种基于现成的轨迹匹配系统，以检测到车辆沿着先前访问的道路沿相反方向行驶的路线时，如何检测位置匹配。我们证明了该方法在26公里的挑战性城市驾驶中的功效，从迄今为止发布的最大的注重雷达的城市自治数据集中，在最近的邻居方法上以高度的精度提高了30％的召回率。
This paper details an application which yields significant improvements to the adeptness of place recognition with Frequency-Modulated Continuous-Wave radar - a commercially promising sensor poised for exploitation in mobile autonomy. We show how a rotationally-invariant metric embedding for radar scans can be integrated into sequence-based trajectory matching systems typically applied to videos taken by visual sensors. Due to the complete horizontal field of view inherent to the radar scan formation process, we show how this off-the-shelf sequence-based trajectory matching system can be manipulated to detect place matches when the vehicle is travelling down a previously visited stretch of road in the opposite direction. We demonstrate the efficacy of the approach on 26 km of challenging urban driving taken from the largest radar-focused urban autonomy dataset released to date -- showing a boost of 30% in recall at high levels of precision over a nearest neighbour approach.
