3D ego-Motion Estimation Using low-Cost mmWave Radars via Radar Velocity Factor for Pose-Graph SLAM
3D ego-Motion Estimation Using low-Cost mmWave Radars via Radar Velocity Factor for Pose-Graph SLAM
复制标题
使用低成本毫米波雷达通过雷达速度因子进行姿态图 SLAM 的 3D 自我运动估计
DOI：
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复制
发表时间：
2021
影响因子：
5.2
通讯作者：
Ayoung Kim
中科院分区：
文献类型：
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作者：
Yeong;Young;Joowan Kim;Ayoung Kim
实现全可视性的通用3D运动估计一直是机器人技术的关键挑战，特别是在极端环境中。广泛采用的基于相机和激光雷达的运动估计在雾或烟雾下严重恶化。在这篇文章中，我们设计了一个独特的传感器系统，用于三维速度估计由两个正交的雷达传感器组成。拟议的配置可以确保地面上的静态物体的返回。这项工作旨在通过将裸露的传感器钻机套入塑料盒中，在恶劣环境中实现真实的传感器部署。如图所示，与现有的基于点匹配的方法相比，所提出的基于速度的自我运动估计具有可靠的性能，而现有的基于点匹配的方法由于套管的原因会导致测量衰减。此外，我们引入了一种新的雷达瞬时速度因子，用于位姿图同步定位和映射（SLAM）框架，并解决了与IMU集成的三维自我运动问题。验证表明，该方法可用于估计室内和室外的一般三维运动，目标是环境中的各种可见性和结构。
Achieving general 3D motion estimation for all-visibility has been a key challenge in robotics, especially in extreme environments. The widely adopted camera and LiDAR-based motion estimation critically deteriorate under fog or smoke. In this letter, we devised a unique sensor system for 3D velocity estimation by compositing two orthogonal radar sensors. The proposed configuration allowed securing returns from the static objects on the ground. This work aimed at a realistic sensor deployment in a harsh environment by casing the bare sensor rig into a plastic box. As will be shown, the proposed velocity-based ego-motion estimation presented reliable performance over existing point matching-based methods, which degraded when measurement attenuates due to the casing. Furthermore, we introduce a novel radar instant velocity factor for pose-graph simultaneous localization and mapping (SLAM) framework and solve for 3D ego-motion in the integration with IMU. The validation reveals that the proposed method can be applied to estimate general 3D motion in both indoor and outdoor, targetting various visibility and the structureness in the environment.