The method of acquiring and processing 3D data from drones

Rutkiewicz, Jan; Malesa, Marcin; Karaszewski, Maciej; Foryś, P.; Siekański, Piotr; Sitnik, Robert

doi:10.1117/12.2319717

Cited by 2 publications

(3 citation statements)

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“…In most of these applications, knowledge of the exact positions of the drone is necessary. These positions can be determined using GPS [3], [6], [7], however, drone GPS accuracy is only in the order of 0.5 -1 m [8]. This accuracy can be improved to single centimeters by using real-time kinematic positioning (RTK) [4].…”

Section: Introductionmentioning

confidence: 99%

A Drone as a Reflector Carrier in Laser Tracker Measurements

Jankowski

Styk

2022

Measurement Science Review

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The paper presents the possibility of mechanizing laser tracker measurements using a drone. Performing measurements using a laser tracker requires touching the measured surface with a probe. Usually it is done manually, even if it requires, e.g., climbing a ladder. The drone was applied as a probe carrier for the laser tracker. To measure a point, the modified drone had to land near this point. Touching the measured surface with the probe was executed using a mobile arm fixed to the drone. This solution allows performing laser tracker measurements without the need of walking or climbing difficult to access surfaces. Two consecutive experiments were performed to verify if such an approach is equally accurate as the standard one (manual measurements). Additionally, the influence of airflow generated by the drones’ propellers on a laser wavelength and the accuracy of interferometric measurements were estimated. The research proves that it is possible to mechanize laser tracker measurements using a drone. Moreover, it is demonstrated that the operating drone does not influence the laser tracker accuracy.

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Section: Introductionmentioning

confidence: 99%

A Drone as a Reflector Carrier in Laser Tracker Measurements

Jankowski

Styk

2022

Measurement Science Review

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“…These systems must be able to detect threats under adverse conditions (e.g., at night when there is not enough light to detect objects) or hidden objects (e.g., persons hiding under the trees who cannot be viewed from above by an ordinary camera). However, because of the differences in thermal radiation, they may be distinguished in the infrared band [1]. 3D data may be helpful in the detection of a relative change in the geometric parameters of the objects.…”

Section: Introductionmentioning

confidence: 99%

“…3D data may be helpful in the detection of a relative change in the geometric parameters of the objects. For instance, masked objects, such as sheds covered by sand or snow, may not be detected using an ordinary visible (VIS) camera; however, they are detectable using 3D data [1]. Therefore, we propose a fusion of data, including color imaging (VIS), thermal imaging (IR), and 3D data (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

Online Correction of the Mutual Miscalibration of Multimodal VIS–IR Sensors and 3D Data on a UAV Platform for Surveillance Applications

et al. 2019

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Unmanned aerial vehicles (UAVs) are widely used to protect critical infrastructure objects, and they are most often equipped with one or more RGB cameras and, sometimes, with a thermal imaging camera as well. To obtain as much information as possible from them, they should be combined or fused. This article presents a situation in which data from RGB (visible, VIS) and thermovision (infrared, IR) cameras and 3D data have been combined in a common coordinate system. A specially designed calibration target was developed to enable the geometric calibration of IR and VIS cameras in the same coordinate system. 3D data are compatible with the VIS coordinate system when the structure from motion (SfM) algorithm is used. The main focus of this article is to provide the spatial coherence between these data in the case of relative camera movement, which usually results in a miscalibration of the system. Therefore, a new algorithm for the detection of sensor system miscalibration, based on phase correlation with automatic calibration correction in real time, is introduced.

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The method of acquiring and processing 3D data from drones

Cited by 2 publications

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A Drone as a Reflector Carrier in Laser Tracker Measurements

A Drone as a Reflector Carrier in Laser Tracker Measurements

Online Correction of the Mutual Miscalibration of Multimodal VIS–IR Sensors and 3D Data on a UAV Platform for Surveillance Applications

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