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Optimizing the Localization of Gamma Radiation Point Sources using a UGV

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU128149" target="_blank" >RIV/00216305:26220/18:PU128149 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/8398368/" target="_blank" >https://ieeexplore.ieee.org/document/8398368/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ELEKTRO.2018.8398368" target="_blank" >10.1109/ELEKTRO.2018.8398368</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Optimizing the Localization of Gamma Radiation Point Sources using a UGV

  • Original language description

    The paper is concerned with the autonomous robotic measurement of gamma radiation and the localization of its sources. The objective is to find techniques that allow faster localization compared to mapping along parallel lines. To achieve this, an unmanned ground vehicle (UGV) is utilized; the device is equipped with a sensitive dual-probe radiation detection system and a module for precise self-localization and navigation. The suggested solution involves exploring the region of interest along circular trajectories and estimating the sources' parameters, the coordinates in particular. The estimation accuracy is then increased using the Gauss-Newton method. The approach was verified through experiments in real conditions; the achieved result consists in a threefold decrease of the time requirement while the localization accuracy remains comparable to that acquired by the radiation mapping. The benefits of the presented research comprise the qualitative expansion of the radiation protection domain and also the applicability of several utilized algorithms in other fields or activities, including, for example, the autonomous robotic inspection of industrial facilities.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20204 - Robotics and automatic control

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    2018 ELEKTRO

  • ISBN

    978-1-5386-4758-5

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    1-6

  • Publisher name

    Neuveden

  • Place of publication

    Neuveden

  • Event location

    Mikulov

  • Event date

    May 21, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000468327400129