融合校准:用于在线外部雷达-摄像头校准的近视角和多跟踪
Lan Cao1, Haiyang Zhu2,3, Tianiyi Gu4
1Shanghai University of Electric Power, Shanghai, 200083, People's Republic of China. caolan@shiep.edu.cn.
Scientific reports
|December 5, 2025
概括
本研究引入了雷达摄像系统的自动在线校准,降低了成本并提高了准确性. 该方法增强了智能交通系统的路边感知.
科学领域:
- 计算机视觉 计算机视觉
- 机器人技术 机器人技术 机器人技术
- 传感器融合式传感器
背景情况:
- 传统的雷达-摄像头校准是劳动密集型和计算成本昂贵的道路边感知.
- 现有的方法在动态环境中难以获得准确性和稳定性.
- 高昂的维护成本阻碍了综合路边感知系统的广泛采用.
研究的目的:
- 开发路边集成雷达摄像头设备的连续在线校准方法.
- 为了减少雷达-摄像头校准中的手动干预和计算开销.
- 为了提高智能运输系统校准的准确性和稳定性.
主要方法:
- 粗度校准使用目标的光心角和其变化速率进行点匹配.
- 精细校准采用匈牙利追踪算法用于相机-雷达点对匹配.
- 实施持续运行和变化适应的验证标准.
主要成果:
- 与手动校准相比,再投影误差减少了25%.
- 与其他自动化方法相比,实现了55%的再投影误差降低.
- 在现实世界中,在交通密集的场景中,证明了增强的校准准确性和稳定性.
结论:
- 拟议的在线校准方法显著提高了准确性并降低了成本.
- 这种方法为动态路边感知挑战提供了强大的解决方案.
- 为推进智能运输系统提供可靠的技术支持.
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