Vision Based UAV Attitude Estimation: Progress and Insights

Shabayek, Abd El Rahman; Demonceaux, Cédric; Morel, Olivier; Fofi, David

doi:10.1007/s10846-011-9588-y

Cited by 73 publications

(23 citation statements)

References 40 publications

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“…Stable unmanned aircraft deserves more efforts [244]. Video stabilization could be integrated into data acquisition systems [245]. In addition, safe operation has become a global concern.…”

Section: Platformsmentioning

confidence: 99%

Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, applications, and prospects

Xiang

Xia

Zhang

2019

IEEE Geosci. Remote Sens. Mag.

140

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The past few decades have witnessed the great progress of unmanned aircraft vehicles (UAVs) in civilian fields, especially in photogrammetry and remote sensing. In contrast with the platforms of manned aircraft and satellite, the UAV platform holds many promising characteristics: flexibility, efficiency, highspatial/temporal resolution, low cost, easy operation, etc., which make it an effective complement to other remote-sensing platforms and a cost-effective means for remote sensing. Considering the popularity and expansion of UAV-based remote sensing in recent years, this paper provides a systematic survey on the recent advances and future prospectives of UAVs in the remote-sensing community. Specifically, the main challenges and key technologies of remote-sensing data processing based on UAVs are discussed and summarized firstly. Then, we provide an overview of the widespread applications of UAVs in remote sensing. Finally, some prospects for future work are discussed. We hope this paper will provide remotesensing researchers an overall picture of recent UAV-based remote sensing developments and help guide the further research on this topic.

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“…Stable unmanned aircraft deserves more efforts [244]. Video stabilization could be integrated into data acquisition systems [245]. In addition, safe operation has become a global concern.…”

Section: Platformsmentioning

confidence: 99%

Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, applications, and prospects

Xiang

Xia

Zhang

2019

IEEE Geosci. Remote Sens. Mag.

140

View full text Add to dashboard Cite

show abstract

“…The skyline (or more precisely, the horizon) has also been investigated as a visual cue for stabilisation in UAVs [19]. However, reliable visual segmentation of sky * First author from terrain using conventional visual wavelength imaging appears difficult [18] particularly in changing weather conditions.…”

Section: Introductionmentioning

confidence: 99%

“…However, because UV-imaging is limited by the filtering in standard camera optics, it has received little further investigation in robotics. In [3] a UV-receiving camera was paired with an omnidirectional mirror, but used to assess the directional information available in the polarisation of UVlight rather than to detect sky per se (sky segmentation by measuring the degree of polarisation of light is suggested in [19]). To our knowledge, there is only one recent investigation [23,24] involving use of a UV-passing filter with a camera to enhance the difference between sky and ground regions, in the context of horizon determination for stabilisation.…”

Section: Introductionmentioning

confidence: 99%

Sky segmentation with ultraviolet images can be used for navigation

Stone¹,

Mangan²,

Ardin³

et al. 2014

Robotics: Science and Systems X

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Abstract-Inspired by ant navigation, we explore a method for sky segmentation using ultraviolet (UV) light. A standard camera is adapted to allow collection of outdoor images containing light in the visible range, in UV only and in green only. Automatic segmentation of the sky region using UV only is significantly more accurate and far more consistent than visible wavelengths over a wide range of locations, times and weather conditions, and can be accomplished with a very low complexity algorithm. We apply this method to obtain compact binary (sky vs non-sky) images from panoramic UV images taken along a 2km route in an urban environment. Using either sequence SLAM or a visual compass on these images produces reliable localisation and orientation on a subsequent traversal of the route under different weather conditions.

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“…An overview of available methods in which horizon detection is used to infer the camera attitude for airborne vehicles is given in (Shabayek, Demonceaux, Morel, & Fofi, ). Work on horizon detection in omnidirectional images is rather limited.…”

Section: Related Workmentioning

confidence: 99%

Highly Accurate Attitude Estimation via Horizon Detection

2015

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Attitude (pitch and roll angle) estimation from visual information is necessary for GPS-free navigation of airborne vehicles. We propose a highly accurate method to estimate the attitude by horizon detection in fisheye images. A Canny edge detector and a probabilistic Hough voting scheme are used to compute an approximate attitude and the corresponding horizon line in the image. Horizon edge pixels are extracted in a band close to the approximate horizon line. The attitude estimates are refined through registration of the extracted edge pixels with the geometrical horizon from a digital elevation map (DEM), in our case the SRTM3 database, extracted at a given approximate position. The proposed method has been evaluated using 1629 images from a flight trial with flight altitudes up to 600 m in an area with ground elevations ranging from sea level up to 500 m. Compared with the ground truth from a filtered inertial measurement unit (IMU)/GPS solution, the standard deviation for the pitch and roll angle errors obtained with 30 Mpixel images are 0.04 • and 0.05 • , respectively, with mean errors smaller than 0.02 • . To achieve the high-accuracy attitude estimates, the ray refraction in the earth's atmosphere has been taken into account. The attitude errors obtained on real images are less or equal to those achieved on synthetic images for previous methods with DEM refinement, and the errors are about one order of magnitude smaller than for any previous vision-based method without DEM refinement. C 2015 Wiley Periodicals, Inc.

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Vision Based UAV Attitude Estimation: Progress and Insights

Cited by 73 publications

References 40 publications

Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, applications, and prospects

Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, applications, and prospects

Sky segmentation with ultraviolet images can be used for navigation

Highly Accurate Attitude Estimation via Horizon Detection

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