针对自动驾驶汽车的多模式传感器系统的联合校准
1Faculty of Electrical Engineering, University of Ljubljana, Tržaška Cesta 25, SI-1000 Ljubljana, Slovenia.
Sensors (Basel, Switzerland)
|July 8, 2023
概括
精确校准多式传感器系统,包括RGB,热和LiDAR,对于现场应用至关重要. 本研究引入了一种系统方法,用于使用LiDAR校准各种相机模式,从而实现精确的数据融合和特征提取.
科学领域:
- 机器人和计算机视觉 机器人和计算机视觉
- 传感器融合式传感器
- 校准技术 校准技术
背景情况:
- 多模式传感器系统对于现场应用至关重要,但由于不同的传感器方式,它们面临着校准挑战.
- 准确的校准对于可靠的数据解释和从RGB,热和LiDAR等多种传感器中提取特征至关重要.
- 现有的方法在交叉模式特征对应方面扎,使传感器校准成为一个悬而未决的问题.
研究的目的:
- 关于LiDAR传感器的多种相机模式 (RGB,热,偏振,双频谱近红外) 的校准,提出一个系统的方法.
- 开发一种适用于任何模式的单摄像头到LiDAR校准的方法.
- 为了在不同的摄像头模式之间建立一个对意识的像素映射,以便无地传输数据.
主要方法:
- 使用平面校准目标对一个LiDAR传感器进行校准各种相机模式 (RGB,热,偏振,双频谱近红外).
- 提出了一种使用LiDAR系统对单个相机进行校准的新方法,可适应任何能够检测校准模式的模式.
- 开发了一种方法,用于在不同的相机类型之间创建对称感知像素映射.
主要成果:
- 通过LiDAR成功展示了一种用于校准各种摄像机模式的系统方法.
- 验证了一种灵活的单摄像头到LiDAR校准方法,在不同类型的传感器中有效.
- 建立了对位移感知映射,使异质相机模式之间能够有效地传输数据和提取特征.
结论:
- 提出的系统方法显著推进了多式联络传感器系统的现场校准.
- 开发的方法促进了准确的数据融合,并使先进的深度学习应用,如跨模式的检测和细分成为可能.
- 这项工作为克服复杂传感器网络中跨模式校准挑战提供了基础方法.
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