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> Robot Localization in Tunnels: Combining Discrete Features in a Pose Graph Framework; 35214292
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Robot Localization in Tunnels: Combining Discrete Features in a Pose Graph Framework; 35214292
Seco, Teresa
;
Lázaro, María T.
;
Espelosín, Jesús
;
Montano, Luis
(Universidad de Zaragoza)
;
Villarroel, José L.
(Universidad de Zaragoza)
Resumen:
Robot localization inside tunnels is a challenging task due to the special conditions of these environments. The GPS-denied nature of these scenarios, coupled with the low visibility, slippery and irregular surfaces, and lack of distinguishable visual and structural features, make traditional robotics methods based on cameras, lasers, or wheel encoders unreliable. Fortunately, tunnels provide other types of valuable information that can be used for localization purposes. On the one hand, radio frequency signal propagation in these types of scenarios shows a predictable periodic structure (periodic fadings) under certain settings, and on the other hand, tunnels present structural characteristics (e.g., galleries, emergency shelters) that must comply with safety regulations. The solution presented in this paper consists of detecting both types of features to be introduced as discrete sources of information in an alternative graph-based localization approach. The results obtained from experiments conducted in a real tunnel demonstrate the validity and suitability of the proposed system for inspection applications. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Idioma:
Inglés
DOI:
10.3390/s22041390
Año:
2022
Publicado en:
Sensors
22, 4 (2022), 1390 - [35 pp]
ISSN:
1424-8220
Factor impacto JCR:
3.9 (2022)
Categ. JCR:
CHEMISTRY, ANALYTICAL
rank: 26 / 86 = 0.302
(2022)
- Q2
- T1
Categ. JCR:
INSTRUMENTS & INSTRUMENTATION
rank: 19 / 63 = 0.302
(2022)
- Q2
- T1
Categ. JCR:
ENGINEERING, ELECTRICAL & ELECTRONIC
rank: 100 / 274 = 0.365
(2022)
- Q2
- T2
Factor impacto CITESCORE:
6.8 -
Engineering
(Q1) -
Chemistry
(Q1) -
Biochemistry, Genetics and Molecular Biology
(Q2) -
Physics and Astronomy
(Q1)
Factor impacto SCIMAGO:
0.764 -
Instrumentation
(Q1) -
Analytical Chemistry
(Q1) -
Medicine (miscellaneous)
(Q2) -
Information Systems
(Q2) -
Biochemistry
(Q2) -
Atomic and Molecular Physics, and Optics
(Q2) -
Electrical and Electronic Engineering
(Q2)
Financiación:
info:eu-repo/grantAgreement/ES/DGA-FSE/T45-20R
Financiación:
info:eu-repo/grantAgreement/ES/MINECO-FEDER/PID2019-105390RB-I00
Tipo y forma:
Article (Published version)
Área (Departamento):
Área Ingen.Sistemas y Automát.
(
Dpto. Informát.Ingenie.Sistms.
)
Exportado de SIDERAL (2024-03-18-13:22:41)
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Notice créée le 2022-05-27, modifiée le 2024-03-19
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