This paper quantifies the performance of visual SLAM that leverages multi-scale fiducial markers (i.e., artificial landmarks that can be detected at a wide range of distances) to show its potential for reliable takeoff and landing navigation in rotorcraft. Prior work has shown that square markers with a black-and-white pattern of grid cells can be used to improve the performance of visual SLAM with color cameras. We extend this prior work to allow nested marker layouts. We evaluate performance during semi-autonomous takeoff and landing operations in a variety of environmental conditions by a DJI Matrice 300 RTK rotorcraft with two FLIR Blackfly color cameras, using RTK GNSS to obtain ground truth pose estimates. Performance measures include absolute trajectory error and the fraction of the number of estimated poses to the total frame. We release all of our results -- our dataset and the code of the implementation of the visual SLAM with fiducial markers -- to the public as open-source.

翻译：本文量化了利用多尺度基准标记（即可在远距离范围内检测的人工地标）的视觉SLAM性能，以展示其在旋翼机可靠起降导航中的潜力。已有研究表明，具有黑白网格单元图案的方形标记可提升彩色相机视觉SLAM的性能。本研究在此基础上扩展，实现了嵌套式标记布局。我们通过搭载两台FLIR Blackfly彩色相机的DJI Matrice 300 RTK旋翼机，在半自主起降操作中评估了多种环境条件下的性能，并利用RTK GNSS获取真实位姿估计。性能指标包括绝对轨迹误差以及估计位姿占总帧数的比例。我们已将全部结果（包括数据集和基于基准标记的视觉SLAM实现代码）作为开源资源向公众开放。