Diverse Planning for UAV Control and Remote Sensing

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00304603" target="_blank" >RIV/68407700:21230/16:00304603 - isvavai.cz</a>

Result on the web

<a href="http://www.mdpi.com/1424-8220/16/12/2199/html" target="_blank" >http://www.mdpi.com/1424-8220/16/12/2199/html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/s16122199" target="_blank" >10.3390/s16122199</a>

Result language

angličtina

Original language name

Diverse Planning for UAV Control and Remote Sensing

Original language description

Unmanned aerial vehicles (UAVs) are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands) to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well) together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

<a href="/en/project/GJ15-20433Y" target="_blank" >GJ15-20433Y: Heuristic Search for Multiagent and Factored Planning</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2016

Confidentiality

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

Name of the periodical

Sensors

ISSN

1424-8220

e-ISSN

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Volume of the periodical

16

Issue of the periodical within the volume

12

Country of publishing house

CH - SWITZERLAND

Number of pages

20

Pages from-to

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UT code for WoS article

000391303000216

EID of the result in the Scopus database

2-s2.0-85007039861