This paper presents OpenREALM, a real-time mapping framework for Unmanned Aerial Vehicles (UAVs). A camera attached to the onboard computer of a moving UAV is utilized to acquire high resolution image mosaics of a targeted area of interest. Different modes of operation allow OpenREALM to perform simple stitching assuming an approximate plane ground, or to fully recover complex 3D surface information to extract both elevation maps and geometrically corrected orthophotos. Additionally, the global position of the UAV is used to georeference the data. In all modes incremental progress of the resulting map can be viewed live by an operator on the ground. Obtained, up-to-date surface information will be a push forward to a variety of UAV applications. For the benefit of the community, source code is public at https://github.com/laxnpander/OpenREALM.
@article{arxiv.2009.10492,
title = {OpenREALM: Real-time Mapping for Unmanned Aerial Vehicles},
author = {Alexander Kern and Markus Bobbe and Yogesh Khedar and Ulf Bestmann},
journal= {arXiv preprint arXiv:2009.10492},
year = {2020}
}
Comments
Full source code on https://github.com/laxnpander/OpenREALM 2020 International Conference on Unmanned Aircraft Systems (ICUAS)