From Event: SPIE Defense + Commercial Sensing, 2019
During the last two decades, several research papers have addressed robust filtering algorithms for the airborne laser scanning (ALS) data. Although most of these filtering algorithms are accurate and robust, they are limited to postprocessing since they rely on complex algorithms and needs high execution time if implemented in an embedded processor. There are number of applications that require generating digital surface models (DSMs) in real-time such as path planning for ground vehicles, where a UAV equipped with a LiDAR scan the terrain ahead to find the path ahead of a ground vehicle. LiDAR scans are also critical to assist with finding the most suitable region for UAV Landing. With the growing demand for safe operation of autonomous systems like UAVs, there is a need for efficient LiDAR processing algorithms capable of generating DSMs in real-time. The aim of this research is to discuss the design of an efficient algorithm that can filter LiDAR point cloud, generate DSM and operate in real-time. The algorithm is suitable for real-time implementation on limited resources embeddedprocessors without the need for a supercomputer. It is also capable of estimating the slope maps from the DSM. The proposed method was successfully implemented in C++ in real-time and was examined in an airborne platform. With comparison to the reference data, we were able to demonstrate the capability of the developed method to distinguish, in real-time, the roofs of the buildings (areas of low slope) from the edges of the same buildings (areas of high slope).
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Ahmed T. Fahmy, Ali Massoud, Aboelmagd M. Noureldin, Sidney Givigi, and Hermann Brassard, "Real-time realization of digital surface models and slope map using lidar for UAV navigation in challenging environment," Proc. SPIE 11005, Laser Radar Technology and Applications XXIV, 110050P (Presented at SPIE Defense + Commercial Sensing: April 17, 2019; Published: 2 May 2019); https://doi.org/10.1117/12.2520804.