Model of Surveillance in Complex Environment Using a Swarm of Unmanned Aerial Vehicles

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG42__%2F21%3A00556834" target="_blank" >RIV/60162694:G42__/21:00556834 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.springer.com/series/558" target="_blank" >https://www.springer.com/series/558</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-70740-8_15" target="_blank" >10.1007/978-3-030-70740-8_15</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Model of Surveillance in Complex Environment Using a Swarm of Unmanned Aerial Vehicles

Popis výsledku v původním jazyce

This paper examines the model of autonomous surveillance using a swarm of unmanned aerial vehicles with the simultaneous detection principle. This model enables to specify a number of sensors needed to detect an object of interest located in the area of interest; objects are detected only if scanned by the specified number of sensors simultaneously. The model plans deployment of individual vehicles in the swarm during the surveillance operation in a such a way that the surveillance is performed in the maximum quality; the quality is measured as a percentage of the area of interest that is covered during the operation. Furthermore, the surveillance is assumed to be conducted in the complex area of operations (including urban environments, build-up areas, or mountain environments with very uneven terrain) where occlusions caused by obstacles or terrain may occur often. For solution, the metaheuristic algorithm based on the simulated annealing is proposed. This algorithm deploys the number of waypoints, from which the monitoring is performed, maximizing the surveillance quality and taking the simultaneous detection principle into consideration. The algorithm is verified by a set of experiments based on typical surveillance scenarios.

Název v anglickém jazyce

Model of Surveillance in Complex Environment Using a Swarm of Unmanned Aerial Vehicles

Popis výsledku anglicky

This paper examines the model of autonomous surveillance using a swarm of unmanned aerial vehicles with the simultaneous detection principle. This model enables to specify a number of sensors needed to detect an object of interest located in the area of interest; objects are detected only if scanned by the specified number of sensors simultaneously. The model plans deployment of individual vehicles in the swarm during the surveillance operation in a such a way that the surveillance is performed in the maximum quality; the quality is measured as a percentage of the area of interest that is covered during the operation. Furthermore, the surveillance is assumed to be conducted in the complex area of operations (including urban environments, build-up areas, or mountain environments with very uneven terrain) where occlusions caused by obstacles or terrain may occur often. For solution, the metaheuristic algorithm based on the simulated annealing is proposed. This algorithm deploys the number of waypoints, from which the monitoring is performed, maximizing the surveillance quality and taking the simultaneous detection principle into consideration. The algorithm is verified by a set of experiments based on typical surveillance scenarios.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISBN

978-3-030-70739-2

ISSN

0302-9743

e-ISSN

1611-3349

Počet stran výsledku

19

Strana od-do

231-249

Název nakladatele

Springer Science and Business Media Deutschland GmbH

Místo vydání

Cham

Místo konání akce

Virtual, Online

Datum konání akce

21. 10. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000763018100015