基于三角目标的外源激光与相机间自动标定

S. Debattisti, L. Mazzei, M. Panciroli
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引用次数: 38

摘要

提出了一种解决室外多传感器车辆摄像机与多层激光扫描仪之间的外部标定问题的方法。本文提出的方法是针对智能车辆在自主导航任务中,由于传感器与目标之间的距离通常与安全相关,因此必须保持不同测量之间的高精度。标定过程利用场景中仍然存在的三角形,在激光和相机参考帧中恢复三个虚拟点作为目标姿态,然后通过最小化图像空间中的几何距离来计算每个相机传感器相对于激光扫描仪的外在信息。为了测试算法的正确性和准确性,使用了一组模拟来报告绝对误差结果和解决方案收敛性,然后基于VIAC原型获得的广泛数据集对鲁棒性和可靠性(即异常值管理)进行测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated extrinsic laser and camera inter-calibration using triangular targets
This paper presents a method for solving the extrinsic calibration between camera and multi-layer laser scanner for outdoor multi-sensorized vehicles. The proposed method is designed for intelligent vehicles within the autonomous navigation task where usually distances between sensor and targets become relevant for safety reasons, therefore high accuracy across different measures must be kept. The calibration procedure takes advantage of triangular shapes still present in scenarios, it recovers three virtual points as target pose in the laser and camera reference frames and then compute extrinsic information of each camera sensor with respect to a laser scanner by minimizing a geometric distance in the image space. To test algorithm correctness, and accuracy a set of simulations are used reporting absolute error results and solution convergence, then tests on robustness and reliability (i.e., outliers management) are based on a wide set of datasets acquired by VIAC prototypes.
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