Application of ultrasonic guided waves to robotic occupancy grid mapping
Tabatabaeipour, Morteza and Trushkevych, Oksana and Dobie, Gordon and Edwards, Rachel S. and McMillan, Ross and MacLeod, Charles and O'Leary, Richard and Dixon, Steven and Gachagan, Anthony and Pierce, Stephen G. (2022) Application of ultrasonic guided waves to robotic occupancy grid mapping. Mechanical Systems and Signal Processing, 163. 108151. ISSN 0888-3270 (https://doi.org/10.1016/j.ymssp.2021.108151)
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Abstract
This paper evaluates the benefits of using ultrasonic guided waves for the mapping of a structure, when implemented on a mobile magnetic robotic platform. It considers the specific problem of mapping geometric features using the guided ultrasonic waves, which enables the localisation of edges and/or the welded joints. Shear Horizontal (SH) guided waves generated by Electro-Magnetic Acoustic Transducers (EMATs) are used for mapping steel samples with a nominal thickness of 10 mm. A Bayesian mapping technique (Occupancy grid mapping) was used to map the boundaries of an irregular sample in a pseudo-pulse-echo mode. The principle is demonstrated in both simulation and laboratory-based experiments. It is shown that the proposed mapping algorithm successfully estimates the position of a sample's edges. Experimentally, a range accuracy of < 1.7 mm (1σ) was achieved on a 1 × 2 m sample using miniaturised EMATs operating at a wavelength of 22 mm.
ORCID iDs
Tabatabaeipour, Morteza, Trushkevych, Oksana, Dobie, Gordon ORCID: https://orcid.org/0000-0003-3972-5917, Edwards, Rachel S., McMillan, Ross, MacLeod, Charles ORCID: https://orcid.org/0000-0003-4364-9769, O'Leary, Richard ORCID: https://orcid.org/0000-0002-4092-2101, Dixon, Steven, Gachagan, Anthony ORCID: https://orcid.org/0000-0002-9728-4120 and Pierce, Stephen G. ORCID: https://orcid.org/0000-0003-0312-8766;-
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Item type: Article ID code: 76775 Dates: DateEvent15 January 2022Published24 June 2021Published Online14 June 2021AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
Strategic Research Themes > Advanced Manufacturing and Materials
Technology and Innovation Centre > Sensors and Asset ManagementDepositing user: Pure Administrator Date deposited: 15 Jun 2021 12:41 Last modified: 21 Nov 2024 01:20 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/76775