On Minimum Aerial Photographs for Planar Region Coverage: Hardness and Approximation

Abstract:Aerial photography with drones often requires covering a planar region with a limited number of images while maximizing image resolution, equivalently minimizing the footprint size of each photograph. We study this task as covering a simple planar polygon with k equal squares or circles of minimum size, including the practically relevant variant in which photograph centers must lie inside the region or on its boundary. We prove that approximating the minimum square side length is NP-hard within a factor of 1.165, and within a factor of 1.25 when square centers are restricted to the region; together with known hardness for circle coverage, these gaps establish strong intractability for aerial coverage planning. We further give a (2\sqrt{2} + \epsilon)-approximation algorithm for square coverage via sampling and farthest-point clustering under the L_\infty metric, which also applies under the center-location constraints. Beyond aerial surveying, the results inform related geometric covering tasks such as facility and sensor placement.

Robotics (cs.RO); Computational Geometry (cs.CG)

arXiv:2512.18268 [cs.RO]

(or arXiv:2512.18268v4 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2512.18268 Focus to learn more arXiv-issued DOI via DataCite

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