22 May 2015 Aircraft path planning for optimal imaging using dynamic cost functions
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Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an “applications lag” for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.
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Gordon Christie, Gordon Christie, Haseeb Chaudhry, Haseeb Chaudhry, Kevin Kochersberger, Kevin Kochersberger, } "Aircraft path planning for optimal imaging using dynamic cost functions", Proc. SPIE 9468, Unmanned Systems Technology XVII, 94680G (22 May 2015); doi: 10.1117/12.2182613; https://doi.org/10.1117/12.2182613

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