一个联合的LiDAR和相机校准算法,基于一个原始的3D校准盘
Ziyang Cui1, Yi Wang1, Xiaodong Chen1
1Key Laboratory of Opto-Electronics Information Technology of Ministry of Education, College of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China.
Sensors (Basel, Switzerland)
|August 14, 2025
概括
这项研究引入了一种新的3D校准板,用于准确的LiDAR相机外部校准. 新方法显著提高了自动驾驶系统的感知能力.
科学领域:
- 机器人和计算机视觉 机器人和计算机视觉
- 自主驾驶系统 自主驾驶系统
背景情况:
- 激光雷达和摄像头之间的精确外部校准对于自动驾驶中的传感器融合至关重要.
- 使用平面或点特征的现有方法具有局限性,导致系统错误和校准精度降低.
研究的目的:
- 开发一种用于LiDAR相机外部校准的新且强大的方法.
- 克服当前校准技术的局限性,提高传感器融合的准确性和稳定性.
主要方法:
- 介绍了一种具有梯度深度,定位标记和角特征的新型3D校准板.
- 使用梯度深度从点云数据准确的3D坐标估计.
- 从图像数据中采集精确的2D像素坐标,使用角特征和定位标记.
主要成果:
- 拟议的方法为增强的激光雷达相机外部校准建立了严格的框架.
- 在模拟环境中的实验结果显示旋转误差低于0.002半径.
- 在模拟环境中的实验结果显示翻译误差低于0.005m.
结论:
- 新的3D校准板和相关方法显著提高了LiDAR相机外部校准的准确性.
- 这一进步有助于实现自动驾驶系统更可靠的感知能力.
- 拟议的方法为关键的传感器融合挑战提供了一个系统和强大的解决方案.
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