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.
翻译:为了部署需要多个感知传感器的自主系统,需要精确和稳健的外部校准。 在本文中,我们提出了一个强大的系统,用于对车辆基框中的多里拉进行实时外部校准,而不需要任何光标或特征。 我们的方法的基础是匹配绝对的全球导航卫星系统和估计的里达尔实时配置。 比较旋转组件使我们能够提高解决办法的稳健性, 而不是仅比较传统的最不平面的翻译组件。 此外, 我们没有比较所有相应的配置, 而是根据我们新的可观察性标准选择由最大相互信息构成的构成。 这使我们能够确定有助于实时校准的一组配置。 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,使用了扫描测试器收集的数据(总共~6.5公里的7个序列)进行了广泛的测试。 本文中显示,我们的方法能够准确确定各种传感器组合的外部校准。