论文标题
高度准确轨迹重建的外部校准
Extrinsic calibration for highly accurate trajectories reconstruction
论文作者
论文摘要
在机器人技术的背景下,准确的基础真相定位是开发映射和本地化算法的基石。在室外环境和长距离的情况下,总站提供了准确,准确的测量结果,这些测量不受日常导航卫星系统(GNSS)准确性的通常因素的影响。虽然单个机器人总站可以在三个自由度(DOF)中跟踪目标的位置,但需要三个机器人总站和三个目标才能产生完整的六个DOF姿势参考。由于表达目标在公共坐标框架中的位置至关重要,因此我们提出了一种新型的外部校准方法,该方法考虑了多个机器人总站,并考虑了现场部署。所提出的方法不需要在系统设置期间手动收集接地控制点,也不需要在每个机器人总站上进行乏味的同步测量。基于广泛的实验工作,我们将我们的方法与用于测量的地理器中使用的经典外部校准方法进行了比较,并证明我们的方法可以在部署过程中节省大量时间。在超过30公里的轨迹上测试,我们的新方法将外部校准的精度提高了25%,而最佳最新方法是手动静态地面控制点的方法。
In the context of robotics, accurate ground-truth positioning is the cornerstone for the development of mapping and localization algorithms. In outdoor environments and over long distances, total stations provide accurate and precise measurements, that are unaffected by the usual factors that deteriorate the accuracy of Global Navigation Satellite System (GNSS). While a single robotic total station can track the position of a target in three Degrees Of Freedom (DOF), three robotic total stations and three targets are necessary to yield the full six DOF pose reference. Since it is crucial to express the position of targets in a common coordinate frame, we present a novel extrinsic calibration method of multiple robotic total stations with field deployment in mind. The proposed method does not require the manual collection of ground control points during the system setup, nor does it require tedious synchronous measurement on each robotic total station. Based on extensive experimental work, we compare our approach to the classical extrinsic calibration methods used in geomatics for surveying and demonstrate that our approach brings substantial time savings during the deployment. Tested on more than 30 km of trajectories, our new method increases the precision of the extrinsic calibration by 25 % compared to the best state-of-the-art method, which is the one taking manually static ground control points.