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Online Drone Coverage of Targets on a Line
by
Pankratov, Denis
, Dobrev, Stefan
, Kranakis, Evangelos
, Narayanan, Lata
, Shende, Sunil
, Georgiou, Konstantinos
, Krizanc, Danny
, Opatrny, Jaroslav
in
Algorithms
/ Competition
/ Lower bounds
/ Upper bounds
2026
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Do you wish to request the book?
Online Drone Coverage of Targets on a Line
by
Pankratov, Denis
, Dobrev, Stefan
, Kranakis, Evangelos
, Narayanan, Lata
, Shende, Sunil
, Georgiou, Konstantinos
, Krizanc, Danny
, Opatrny, Jaroslav
in
Algorithms
/ Competition
/ Lower bounds
/ Upper bounds
2026
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Paper
Online Drone Coverage of Targets on a Line
2026
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Overview
We study a problem of online targets coverage by a drone or a sensor that is equipped with a camera or an antenna of fixed half-angle of view \\(\\). The targets to be monitored appear at arbitrary positions on a line barrier in an online manner. When a new target appears, the drone has to move to a location that covers the newly arrived target, as well as already existing targets. The objective is to design a coverage algorithm that optimizes the total length of the drone's trajectory. Our results are reported in terms of an algorithm's competitive ratio, i.e., the worst-case ratio (over all inputs) of its cost to that of an optimal offline algorithm. In terms of upper bounds, we present three online algorithms and prove bounds on their competitive ratios for every \\( ın [0, /2]\\). The best of them, called is significantly better than the other two for \\(/6 < < /3\\). In particular, for \\(=/4\\), its worst case, has competitive ratio \\(1.25\\), while the other two have competitive ratio \\(2\\). Finally, we prove a lower bound on the competitive ratio of online algorithms for a drone with half-angle \\( ın [0, /4]\\); this bound is a function of \\(\\) that achieves its maximum value at \\( = /4\\) equal to \\((1+2)/2 1.207\\).
Publisher
Cornell University Library, arXiv.org
Subject
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