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Marker-Less Micro Aerial Vehicle Detection and Localization Using Convolutional Neural Networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00341811" target="_blank" >RIV/68407700:21230/20:00341811 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/LRA.2020.2972819" target="_blank" >https://doi.org/10.1109/LRA.2020.2972819</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/LRA.2020.2972819" target="_blank" >10.1109/LRA.2020.2972819</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Marker-Less Micro Aerial Vehicle Detection and Localization Using Convolutional Neural Networks

  • Original language description

    A relative localization system for micro aerial vehicles (MAVs), which is able to work without any markers or other specialized equipment, is presented in this letter. The system utilizes images from an onboard camera to detect nearby MAVs using a convolutional neural network. When compared to traditional computer vision-based relative localization systems, this approach removes the need for specialized markers to be placed on the MAVs, saving weight and space, while also enabling localization of noncooperating robots. The system is designed and implemented to run online, onboard an MAV platform in order to enable relative stabilization of several MAVs in a formation or swarm-like behavior, when operating in a closed feedback loop with the control system of the MAVs. We demonstrate the viability and robustness of the proposed method in real-world experiments. The method was also designed for the purpose of autonomous aerial interception and is a fitting complement to other MAV detection and relative localization methods for this purpose, as is shown in the experiments.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

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

Others

  • Publication year

    2020

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    IEEE Robotics and Automation Letters

  • ISSN

    2377-3766

  • e-ISSN

    2377-3766

  • Volume of the periodical

    5

  • Issue of the periodical within the volume

    2

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    8

  • Pages from-to

    2459-2466

  • UT code for WoS article

    000526521500006

  • EID of the result in the Scopus database

    2-s2.0-85081044731