Path planning algorithm ensuring accurate localization of radiation sources

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/68407700:21730/22:00354308

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Path planning algorithm ensuring accurate localization of radiation sources

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Path planning algorithm ensuring accurate localization of radiation sources

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

<a href="/cs/project/EF15_003%2F0000470" target="_blank" >EF15_003/0000470: Robotika pro Průmysl 4.0</a><br>

Návaznosti

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

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Applied Intelligence

ISSN

0924-669X

e-ISSN

1573-7497

Svazek periodika

52

Číslo periodika v rámci svazku

January

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

23

Strana od-do

9574-9596

Kód UT WoS článku

000739812700005

EID výsledku v databázi Scopus

2-s2.0-85122408941