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LIDAR-based Stabilization, Navigation and Localization for UAVs Operating in Dark Indoor Environments

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00353985" target="_blank" >RIV/68407700:21230/21:00353985 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/ICUAS51884.2021.9476837" target="_blank" >https://doi.org/10.1109/ICUAS51884.2021.9476837</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ICUAS51884.2021.9476837" target="_blank" >10.1109/ICUAS51884.2021.9476837</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    LIDAR-based Stabilization, Navigation and Localization for UAVs Operating in Dark Indoor Environments

  • Original language description

    Autonomous operation of UAVs in a closed environment requires precise and reliable pose estimate that can stabilize the UAV without using external localization systems such as GNSS. In this work, we are concerned with estimating the pose from laser scans generated by an inexpensive and lightweight LIDAR. We propose a localization system for lightweight (under 200 g) LIDAR sensors with high reliability in arbitrary environments, where other methods fail. The general nature of the proposed method allows deployment in wide array of applications. Moreover, seamless transitioning between different kinds of environments is possible. The advantage of LIDAR localization is that it is robust to poor illumination, which is often challenging for camera-based solutions in dark indoor environments and in the case of the transition between indoor and outdoor environment. Our approach allows executing tasks in poorly-illuminated indoor locations such as historic buildings and warehouses, as well as in the tight outdoor environment, such as forest, where vision-based approaches fail due to large contrast of the scene, and where large well-equipped UAVs cannot be deployed due to the constrained space.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20204 - Robotics and automatic control

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

    2021

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2021 International Conference on Unmanned Aircraft Systems (ICUAS)

  • ISBN

    978-0-7381-3115-3

  • ISSN

    2373-6720

  • e-ISSN

    2575-7296

  • Number of pages

    9

  • Pages from-to

    243-251

  • Publisher name

    IEEE Xplore

  • Place of publication

  • Event location

    Athens

  • Event date

    Jun 15, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article