用2D成像雷达+陀螺仪实现激光雷达级3D运动估计
3DRO: Lidar-level SE(3) Direct Radar Odometry Using a 2D Imaging Radar and a Gyroscope
- 基于2D雷达速度与3D陀螺仪数据融合，扩展传统2D定位到3D空间
- 在Boreas-RT数据集上跑643公里，精度达激光雷达级别
- 适合需要低成本高精度3D定位的自动驾驶与机器人系统
近年来，机器人领域重新关注基于雷达的感知与状态估计。2D成像雷达能提供环境的稠密360度信息。尽管雷达天线存在发射与接收的锥形范围，其采集数据通常被假设局限于垂直于雷达旋转轴的平面。因此，多数基于2D成像雷达的方法仅能进行SE(2)状态估计。本文提出3DRO，将原有的SE(2)直接雷达里程计（DRO）框架扩展至SE(3)状态估计。虽然仍沿用DRO的2D速度估计并假设数据平面性，但通过在SO(3)上融合3D陀螺仪测量，实现了对SE(3)自身运动的估计。该方法虽简单，但在643公里的Boreas-RT数据集上验证了其达到激光雷达级别的里程计精度。
原文摘要 · Abstract (English)
Recently, the robotics community has regained interest in radar-based perception and state estimation. A 2D imaging radar provides dense 360deg information about the environment. Despite the radar antenna's cone of emission and reception, the collected data is generally assumed to be limited to the plane orthogonal to the radar's spinning axis. Accordingly, most methods based on 2D imaging radars only perform SE(2) state estimation. This paper presents 3DRO, an extension of the SE(2) Direct Radar Odometry (DRO) framework to perform state estimation in SE(3). While still assuming planarity of the data through DRO's 2D velocity estimates, it integrates 3D gyroscope measurements over SO(3) to estimate SE(3) ego motion. While simple, this approach provides lidar-level odometry accuracy as demonstrated using 643km of data from the Boreas-RT dataset.
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