Closed loop-based extrinsic calibration of multi-modal sensors

Sungdae Sim, K. Kwak, J. Kim, Sanghyun Joo
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引用次数: 5

Abstract

By increasing the requirement of reliable and accurate sensor information, the integration of multiple sensors has gained attention. Especially, the fusion of a LIDAR(Light Detection And Ranging) and a camera is one of the sensor combination broadly used because it provides the complementary and redundant information. Many existing calibration approaches consider the problem estimating the relative pose between each sensor pair such as a LIDAR and a camera. However, these approaches do not provide accurate solutions for multisensor configurations such as a LIDAR and cameras or LIDARs and cameras. In this paper, we propose a new extrinsic calibration algorithm using closed-loop constraints for multi-modal sensor configuration. The extrinsic calibration parameters are estimated by minimizing the distance between corresponding features projected onto the image plane. We conduct several experiments to evaluate the performance of our approach, such as comparison of the RMS distance of the ground truth and the projected points, and comparison between the independent sensor pair and our approach.
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基于闭环的多模态传感器外部定标
随着对传感器信息可靠性和准确性要求的不断提高,多传感器的集成得到了人们的关注。特别是激光雷达(LIDAR, Light Detection And Ranging)与相机的融合,由于其提供了互补和冗余的信息,是目前应用广泛的传感器组合之一。许多现有的校准方法都考虑了每个传感器对(如激光雷达和相机)之间的相对姿态估计问题。然而,这些方法并不能为多传感器配置提供精确的解决方案,如激光雷达和摄像头或激光雷达和摄像头。本文提出了一种基于闭环约束的多模态传感器外部标定算法。通过最小化投影到图像平面上的相应特征之间的距离来估计外部校准参数。我们进行了几个实验来评估我们的方法的性能,例如地面真值和投影点的均方根距离的比较,以及独立传感器对与我们的方法之间的比较。
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