With recent and ongoing improvements to unmanned aerial vehicle (UAV) endurance and availability, they are in a unique position to provide long term surveillance in risky environments. This paper presents a swarm intelligence algorithm for executing an exhaustive and persistent search of a non-trivial area of interest using a decentralized UAV swarm without long range communication. The algorithm allows for an environment containing arbitrary arrangements of no-fly zones, non-uniform levels of priority and dynamic priority changes in response to target acquisition or external commands. Performance is quantitatively analysed via comparative simulation with another leading algorithm of its class. © Springer-Verlag Berlin Heidelberg 2009.
CITATION STYLE
Howden, D. (2009). Continuous swarm surveillance via distributed priority maps. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5865 LNAI, pp. 221–231). https://doi.org/10.1007/978-3-642-10427-5_22
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