108579 20230519145356.0 doi 10.1016/j.robot.2020.103702 sideral 122361 ART-2021-122361 eng Rizzo, C. An alternative approach for robot localization inside pipes using RF spatial fadings 2021 Access copy available to the general public Unrestricted 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. info:eu-repo/grantAgreement/ES/DGA/T45-17R info:eu-repo/grantAgreement/ES/MINECO-AEI-FEDER/DPI2016-76676-R info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 3.7 2021 ROBOTICS 14 / 30 = 0.467 2021 Q2 T2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 67 / 146 = 0.459 2021 Q2 T2 AUTOMATION & CONTROL SYSTEMS 27 / 65 = 0.415 2021 Q2 T2 1.202 2021 Computer Science Applications 2021 Q1 Software 2021 Q1 Control and Systems Engineering 2021 Q1 8.1 2021 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Seco, T. Espelosín, J. Lera, F. Universidad de Zaragoza (orcid)0000-0002-1568-1481 Villarroel, J.L. Universidad de Zaragoza (orcid)0000-0002-7148-4642 5007 520 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Ingen.Sistemas y Automát. 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 136 (2021), 103702 [20 pp] Robot. auton. syst. ROBOTICS AND AUTONOMOUS SYSTEMS 0921-8890 2193915 http://zaguan.unizar.es/record/108579/files/texto_completo.pdf Postprint 943879 http://zaguan.unizar.es/record/108579/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:108579 articulos driver 2023-05-18-13:32:36 ARTICLE