为非重叠的双LiDAR系统使用2.5D校准框架进行基于GPIS的校准
Huan Yu1, Xiaohong Zhang2,3, Ming Li4
1School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China.
Sensors (Basel, Switzerland)
|February 13, 2026
概括
这项研究引入了双LiDAR系统的新2.5D校准框架,提高了非重叠视野的自动驾驶精度. 该方法提高了稳定性和精度,而不需要校准目标.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 计算机视觉 计算机视觉
- 传感器融合式传感器
背景情况:
- 双LiDAR系统的外部校准对于自动驾驶至关重要.
- 不重叠的视野 (FoV) 对传统校准方法构成重大挑战.
- 在空间重叠有限的场景中,基于对应的技术往往不可靠.
研究的目的:
- 为双LiDAR系统开发一个以工程为导向的2.5D校准框架.
- 为了应对在非重叠的FoV配置中外部校准的挑战.
- 为了提高双LiDAR校准的准确性,稳定性和可行性.
主要方法:
- 一种以运动为导向的平面对齐方法估计了初始的水平外观 (x, y, yaw).
- 斯过程隐性表面 (GPIS) 用于通过空间分离扫描来精炼外在表面.
- 该框架避免了校准目标,并减少了对强有力的场景假设的依赖.
主要成果:
- 在高准确度模拟中实现了厘米级的横向精度和小度的曲率误差.
- 在各种噪音条件下,与基于运动和基于鸟眼视图 (BEV) 的基线相比,表现一致优异.
- 预先的nuScenes研究显示,在模拟的不重叠的双LiDAR设置中,改进了准确度和竞争力的横向精度.
结论:
- 拟议的2.5D校准框架为不重叠的双LiDAR系统提供了一个实际的解决方案.
- 该方法提供了准确性,稳定性和工程可行性的有利平衡.
- 它作为一个有效的完善阶段,用于增强双LiDAR校准.
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