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Infrastructure Monitoring: Automated Flight Path Optimization using Targeted Object Reconstruction Improvement


In the current application of targeted multi-scale flight path optimization and infrastructure monitoring, we have observed that there are always 3D objects in the scene that detract from the object(s) of interest or are “not allowed” for imaging (e.g., privacy). The existing multi-scale flight path optimization algorithms incorporated into our site monitoring app Volare currently have a 100,000-face limit on the prior mesh model that can be processed and optimized for the sake of speed. This proposed extension of the Infrastructure Monitoring Project in the C-UAS would focus expanding the capabilities of these algorithms to focus specifically on 3D objects of interest in the scene rather than just on general areas. An example might include focusing the optimized images on a desired building rather than the landscaping trees outside and around the building. For Year 1, we propose to focus on proof-of-concept by using controlled simulation and progressive additions to the current flight path optimization algorithms to focus on desired 3D objects in a scene. For Year 2, we propose to begin controlled field testing of the algorithms, debugging, and incorporation into the Volare app. For Year 3, we propose rigorous field tests and controlled field comparisons against existing flight path optimization solutions (including our current Volare solution and commercial off-the-shelf solutions).



Center for Unmanned Aircraft Systems: https://c-uas.org
BYU Roam: https://roam.byu.edu