Vision-Based Odometry and SLAM for Medium and High Altitude Flying UAVs
Vision-Based Odometry and SLAM for Medium and High Altitude Flying UAVs
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DOI：
10.1007/s10846-008-9257-y
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发表时间：
2009-03-01
影响因子：
3.3
通讯作者：
Ollero, A.
中科院分区：
文献类型：
--
作者：
Caballero, F.;Merino, L.;Ollero, A.
本文提出了一种基于视觉的机载摄像机无人机定位技术。只考虑特征跟踪算法提供的自然地标，没有视觉信标或已知位置的地标的帮助。首先，介绍了一种单目视觉里程计，当GPS精度降低到临界水平时，它可以作为备用系统。利用机载摄像机采集的图像，利用基于同形图的技术计算无人机的相对平移和旋转。在分析问题时考虑到估计的随机性和实际实施问题。然后将视觉里程计集成到同时定位和映射（SLAM）方案中，以减少基于里程计的位置估计方法中累积误差的影响。提出了一种新的无人机SLAM预测和地标初始化方法。该论文得到了广泛的实验工作的支持，其中所提出的算法已经使用真实的无人机进行了测试和验证。
This paper proposes vision-based techniques for localizing an unmanned aerial vehicle (UAV) by means of an on-board camera. Only natural landmarks provided by a feature tracking algorithm will be considered, without the help of visual beacons or landmarks with known positions. First, it is described a monocular visual odometer which could be used as a backup system when the accuracy of GPS is reduced to critical levels. Homography-based techniques are used to compute the UAV relative translation and rotation by means of the images gathered by an onboard camera. The analysis of the problem takes into account the stochastic nature of the estimation and practical implementation issues. The visual odometer is then integrated into a simultaneous localization and mapping (SLAM) scheme in order to reduce the impact of cumulative errors in odometry-based position estimation approaches. Novel prediction and landmark initialization for SLAM in UAVs are presented. The paper is supported by an extensive experimental work where the proposed algorithms have been tested and validated using real UAVs.