Abstract: In the last two decades, unmanned aircraft systems (UAS) were successfully used in different environments for diverse applications like territorial mapping, heritage 3D documentation, as built surveys, construction monitoring, solar panel placement and assessment, road inspections, etc. These applications were correlated to the onboard sensors like RGB cameras, multi-spectral cameras, thermal sensors, panoramic cameras, or LiDARs. According to the different onboard sensors, individual flight planning is required to satisfy the characteristics of the sensor and the project aims.
For UAS LiDAR-based mapping missions, requirements for the flight planning are different with respect to conventional UAS image-based flight plans because of different reasons related to the LiDAR scanning mechanism, scanning range, output scanning rate, field of view (FOV), rotation speed, etc. Although flight planning for image-based UAS missions is a well-known and solved problem, flight planning for a LiDAR-based UAS mapping is still an open research topic that needs further investigations.
The article presents the developments of a LiDAR-based UAS flight planning tool, tested with simulations in real scenarios. The flight planning simulations considered an UAS platform equipped, alternatively, with three low-cost multi-beam LiDARs, namely Quanergy M8, Velodyne VLP-16, and the Ouster OS-1-16. The specific characteristics of the three sensors were used to plan flights and acquired dense point clouds. Comparisons and analyses of the results showed clear relationships between point density, flying speeds, and flying heights.
From a research paper in the International Journal of Geo-Information by Bashar Alsadik and Fabio Remondino.
In this paper, a LiDAR-based UAS flight planning topic was introduced, with a clear mathematical formulation. A prototype software was built using MATLAB and it was shared with the community. Simulations and experiments were performed using three low-cost multi-beam LiDAR sensors—Velodyne VLP-16, Quanergy M8, and Ouster OS-1-16.
The paper showed the ability to scan an urban region using a LiDAR sensor in a nadir orientation, or to scan tall structures, like towers and buildings, considering a 90° tilted LiDAR sensor.
Regarding the first research question of the paper, in order to compute the UAS waypoints we need only sidelap, flying height, speed, area of interest, and the LiDAR type. Answers were also given regarding the estimation of the point density in an urban region at different flying heights, sidelaps, and flying speeds, using the selected three low-cost multi-beam LiDAR sensors. Graphical plots were presented to illustrate the relation between point densities and sidelap percentages, at different flying heights and speeds.
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