无需假设地面平坦，实现车载激光雷达与惯导在倾斜路面的精准标定
Extending Ground-Constraint LiDAR-IMU Calibration to Tilted Surfaces in a Continuous-Time Framework
- 提出新型地面平面残差，不依赖重力与地面法向共线假设
- 在倾斜和水平路面上均提升标定重复性，倾斜场景改进更显著
- 适用于越野车等非平坦地形，开源代码已发布
本文提出一种新方法，将无目标激光雷达-惯导标定扩展至非平面环境。传统标定需传感器充分运动，而地面车辆正常行驶难以满足此条件。现有方法依赖重力方向与地面法向共线假设，仅适用于平坦地面。本文设计的地面平面残差不依赖该假设，适用于倾斜表面的平面运动。实验在Husky地面车辆、M2DGR数据集及越野车数据集上验证，结果表明在倾斜与平坦场景下重复性均提升，尤其在倾斜情况下改善明显。代码与实验已开源。
原文摘要 · Abstract (English)
This paper presents a novel method that extends targetless LiDAR-IMU calibration for ground vehicles to non- flat environments. Calibration typically necessitates full exci- tation of the sensor rig, a requirement that is not fulfilled by ground vehicles in normal operation. To address the degenerate planar motion, state-of-the-art methods propose residuals that assume the colinearity of the gravity and physical surface normal vectors, restricting usage to cases where the ground is assumed flat. This paper proposes ground-plane residuals that do not require this assumption, and are applicable for planar motion on a tilted surface. Results are demonstrated on a dataset collected from a Husky ground vehicle, on the M2DGR dataset, as well as on an offroad vehicle dataset. Repeatability is shown to be improved both in tilted and flat-ground scenarios, with strong improvement demonstrated for the tilted case. The implementation and experiments are open-sourced at https://github.com/vkorotkine/licalib_tilted_ground.
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