论文标题
ECTLO：使用较小FOV的LIDAR的范围图像有效连续时射仪
ECTLO: Effective Continuous-time Odometry Using Range Image for LiDAR with Small FoV
论文作者
论文摘要
基于棱镜的LIDAR比传统的机械多线旋转激光雷达更紧凑，更便宜，最近在机器人技术中变得越来越流行。但是，对于这些新的LiDAR传感器，包括较小的视野，严重的运动扭曲和不规则模式存在一些挑战，这些挑战实际上阻碍了它们被广泛用于激光雷达的探测仪。为了解决这些问题，我们为基于Risley-Prism的LIDAR提供了一种有效的连续时间激光镜（ECTLO）方法，具有非重复扫描模式。通过有效的地图表示，采用了涵盖LiDAR小型FOV中历史点的单个范围图像。为了说明MAP更新后闭塞的嘈杂数据，将基于滤波器的平面高斯混合物模型用于强大的注册。此外，采用仅开激光的连续运动模型来缓解不可避免的扭曲。已经使用具有不同扫描模式的基于棱镜的激光雷达对各种测试台进行了广泛的实验，其有前途的结果证明了我们提出的方法的功效。
Prism-based LiDARs are more compact and cheaper than the conventional mechanical multi-line spinning LiDARs, which have become increasingly popular in robotics, recently. However, there are several challenges for these new LiDAR sensors, including small field of view, severe motion distortions, and irregular patterns, which hinder them from being widely used in LiDAR odometry, practically. To tackle these problems, we present an effective continuous-time LiDAR odometry (ECTLO) method for the Risley-prism-based LiDARs with non-repetitive scanning patterns. A single range image covering historical points in LiDAR's small FoV is adopted for efficient map representation. To account for the noisy data from occlusions after map updating, a filter-based point-to-plane Gaussian Mixture Model is used for robust registration. Moreover, a LiDAR-only continuous-time motion model is employed to relieve the inevitable distortions. Extensive experiments have been conducted on various testbeds using the prism-based LiDARs with different scanning patterns, whose promising results demonstrate the efficacy of our proposed approach.
