An alternative approach for robot localization inside pipes using RF spatial fadings

Rizzo, C. ; Seco, T. ; Espelosín, J. ; Lera, F. (Universidad de Zaragoza) ; Villarroel, J.L. (Universidad de Zaragoza)

Resumen: Accurate robot localization represents a challenge inside pipes due to the particular conditions that characterize this type of environment. Outdoor techniques (GPS in particular) do not work at all inside metal pipes, while traditional indoor localization methods based on camera or laser sensors do not perform well mainly due to a lack of external illumination and distinctive features along pipes. Moreover, humidity and slippery surfaces make wheel odometry unreliable. In this paper, we estimate the localization of a robot along a pipe with an alternative Radio Frequency (RF) approach. We first analyze wireless propagation in metallic pipes and propose a series of setups that allow us to obtain periodic RF spatial fadings (a sort of standing wave periodic pattern), together with the influence of the antenna position and orientation over these fadings. Subsequently, we propose a discrete RF odometry-like method, by means of counting the fadings while traversing them. The transversal fading analysis (number of antennas and cross-section position) makes it possible to increase the resolution of this method. Lastly, the model of the signal is used in a continuous approach serving as an RF map. The proposed localization methods outperform our previous contributions in terms of resolution, accuracy, reliability and robustness. Experimental results demonstrate the effectiveness of the RF-based strategy without the need for a previously known map of the scenario or any substantial modification of the existing infrastructure.

Idioma: Inglés

DOI: 10.1016/j.robot.2020.103702

Año: 2021

Publicado en: ROBOTICS AND AUTONOMOUS SYSTEMS 136 (2021), 103702 [20 pp]
ISSN: 0921-8890

Factor impacto JCR: 3.7 (2021)

Categ. JCR: ROBOTICS rank: 14 / 30 = 0.467 (2021) - Q2 - T2
Categ. JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE rank: 67 / 146 = 0.459 (2021) - Q2 - T2
Categ. JCR: AUTOMATION & CONTROL SYSTEMS rank: 27 / 65 = 0.415 (2021) - Q2 - T2

Factor impacto CITESCORE: 8.1 - Engineering (Q1) - Mathematics (Q1) - Computer Science (Q1)

Factor impacto SCIMAGO: 1.202 - Computer Science Applications (Q1) - Software (Q1) - Control and Systems Engineering (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/T45-17R
Financiación: info:eu-repo/grantAgreement/ES/MINECO-AEI-FEDER/DPI2016-76676-R

Tipo y forma: Artículo (PostPrint)

Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)
Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)