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Path planning algorithm ensuring accurate localization of radiation sources

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00354308" target="_blank" >RIV/68407700:21230/22:00354308 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21730/22:00354308

  • Result on the web

    <a href="https://doi.org/10.1007/s10489-021-02941-y" target="_blank" >https://doi.org/10.1007/s10489-021-02941-y</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s10489-021-02941-y" target="_blank" >10.1007/s10489-021-02941-y</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Path planning algorithm ensuring accurate localization of radiation sources

  • Original language description

    An autonomous search for sources of gamma radiation in an outdoor environment is a domain suitable for the deployment of a heterogeneous robotic team, consisting of an Unmanned Aerial (UAV) and an Unmanned Ground (UGV) Vehicle. The UAV is convenient for fast mapping of the area and identifying regions of interest, whereas the UGV can perform highly accurate localization. It is assumed that the regions of interest are identified by the UAV during an initial reconnaissance, while performing a simple motion pattern. This paper proposes a path planning algorithm for the UGV, which guarantees accurate source localization in multiple preselected regions and minimizes the total path length. The problem is formulated as the Generalized Travelling Salesman Problem (GTSP) defined for discrete sets of suitable maneuvers (circular arcs), ensuring source localization in the given regions. The problem is successfully solved by a modified version of the state of the art GTSP solver, Generalized Large Neighborhood Search with Arcs (GLNSarc). Apart from adapting the GLNS, other aspects of the planning task are addressed: problem discretization and informed sampling of valid circular arcs, variants of weighting the nonrestricted trajectory segments between the arcs and postprocessing of the discretely planned trajectory in the continuous domain.

  • 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

    20204 - Robotics and automatic control

Result continuities

  • Project

    <a href="/en/project/EF15_003%2F0000470" target="_blank" >EF15_003/0000470: Robotics 4 Industry 4.0</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Applied Intelligence

  • ISSN

    0924-669X

  • e-ISSN

    1573-7497

  • Volume of the periodical

    52

  • Issue of the periodical within the volume

    January

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    23

  • Pages from-to

    9574-9596

  • UT code for WoS article

    000739812700005

  • EID of the result in the Scopus database

    2-s2.0-85122408941