论文标题
可观察性感知在线多大级别外部校准
Observability-aware online multi-lidar extrinsic calibration
论文作者
论文摘要
对于需要多个传感器才能感知的自主系统是必要的，精确且鲁棒的外部校准是必需的。在本文中，我们提出了一个强大的系统，用于在车辆底架中对多个激光射击的实时外部校准，而无需任何基金标记或功能。我们以匹配绝对GNSS和估计的LiDAR实时构成的方法为基础。比较旋转组件使我们能够提高解决方案的鲁棒性，而不是传统的最小二乘方法比较翻译组件。此外，我们没有比较所有相应的姿势，而是根据我们的新可观察性标准选择包含最大相互信息的姿势。这使我们能够确定对实时校准有用的姿势子集。我们还提供了确保校准完成的停止标准。为了验证我们的方法，对使用Scania测试车的数据进行了广泛的测试（7个序列，总计约6.5 km）。本文中介绍的结果表明，我们的方法能够准确确定传感器设置各种组合的外部校准。
Accurate and robust extrinsic calibration is necessary for deploying autonomous systems which need multiple sensors for perception. In this paper, we present a robust system for real-time extrinsic calibration of multiple lidars in vehicle base frame without the need for any fiducial markers or features. We base our approach on matching absolute GNSS and estimated lidar poses in real-time. Comparing rotation components allows us to improve the robustness of the solution than traditional least-square approach comparing translation components only. Additionally, instead of comparing all corresponding poses, we select poses comprising maximum mutual information based on our novel observability criteria. This allows us to identify a subset of the poses helpful for real-time calibration. We also provide stopping criteria for ensuring calibration completion. To validate our approach extensive tests were carried out on data collected using Scania test vehicles (7 sequences for a total of ~ 6.5 Km). The results presented in this paper show that our approach is able to accurately determine the extrinsic calibration for various combinations of sensor setups.
