A study on low-cost sensor fusion for automatic railway coupler inspection

Randika K.W. Vithanage; Colin S. Harrison; Anjali K.M. DeSilva

doi:10.1109/CEEC.2018.8674237

A study on low-cost sensor fusion for automatic railway coupler inspection

Randika K.W. Vithanage^*, Colin S. Harrison, Anjali K.M. DeSilva

^*Corresponding author for this work

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper presents findings of a case study conducted to introduce industrial robots into the inspection process of the electrical connector panel in automatic railway couplers. Detection and localization of smaller components in a highly unstructured and dynamic environment similar to a railway maintenance workshop is a non-trivial task. Therefore, a visual perception solution equipped with depth and RGB sensing hardware is suggested. The proposed solution is robust to environmental noise and precise positioning of the target with respect to the camera is not required. The accuracy of the overall system and robustness of the proposed solution are validated with the aid of well-established methodologies, data found in literature and on the actual coupler in usual working environments.

Original language	English
Title of host publication	2018 10th Computer Science and Electronic Engineering (CEEC)
Publisher	IEEE
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781538672754
ISBN (Print)	9781538672761
DOIs	https://doi.org/10.1109/CEEC.2018.8674237
Publication status	Published - 28 Mar 2019

Keywords

sensor fusion
railway maintenance
robotic vision

Documents and Links

10.1109/CEEC.2018.8674237

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title = "A study on low-cost sensor fusion for automatic railway coupler inspection",

abstract = "This paper presents findings of a case study conducted to introduce industrial robots into the inspection process of the electrical connector panel in automatic railway couplers. Detection and localization of smaller components in a highly unstructured and dynamic environment similar to a railway maintenance workshop is a non-trivial task. Therefore, a visual perception solution equipped with depth and RGB sensing hardware is suggested. The proposed solution is robust to environmental noise and precise positioning of the target with respect to the camera is not required. The accuracy of the overall system and robustness of the proposed solution are validated with the aid of well-established methodologies, data found in literature and on the actual coupler in usual working environments.",

keywords = "sensor fusion, railway maintenance, robotic vision",

author = "Vithanage, {Randika K.W.} and Harrison, {Colin S.} and DeSilva, {Anjali K.M.}",

note = "Acceptance and AAM req'd 12/12/19 DC and chaser 31/1/20 ET AAM: author provided version we can't use 18/6/20 requested AAM. ET Acceptance date (in SAN): author confirmed month and year; used last date in month – ET 18/6/20",

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AU - DeSilva, Anjali K.M.

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PY - 2019/3/28

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N2 - This paper presents findings of a case study conducted to introduce industrial robots into the inspection process of the electrical connector panel in automatic railway couplers. Detection and localization of smaller components in a highly unstructured and dynamic environment similar to a railway maintenance workshop is a non-trivial task. Therefore, a visual perception solution equipped with depth and RGB sensing hardware is suggested. The proposed solution is robust to environmental noise and precise positioning of the target with respect to the camera is not required. The accuracy of the overall system and robustness of the proposed solution are validated with the aid of well-established methodologies, data found in literature and on the actual coupler in usual working environments.

AB - This paper presents findings of a case study conducted to introduce industrial robots into the inspection process of the electrical connector panel in automatic railway couplers. Detection and localization of smaller components in a highly unstructured and dynamic environment similar to a railway maintenance workshop is a non-trivial task. Therefore, a visual perception solution equipped with depth and RGB sensing hardware is suggested. The proposed solution is robust to environmental noise and precise positioning of the target with respect to the camera is not required. The accuracy of the overall system and robustness of the proposed solution are validated with the aid of well-established methodologies, data found in literature and on the actual coupler in usual working environments.

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KW - railway maintenance

KW - robotic vision

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