Localisation of a mobile robot for bridge bearing inspection

Peel, H, Luo, S ORCID: 0000-0003-4760-0372, Cohn, AG and Fuentes, R (2018) Localisation of a mobile robot for bridge bearing inspection. AUTOMATION IN CONSTRUCTION, 94. pp. 244-256.

Text 1-s2.0-S0926580517303916-main (1).pdf - Published version Download (4MB)

Abstract

Bridge bearings are a critical component of a bridge and require regular visual inspection to ensure the safe operation of the bridge throughout its life. However, the bearings are often located in spaces that are difficult or hazardous to reach, which can impact how often the bearings are inspected. In addition, these spaces are small and offer significant challenges for tele-operation due to line-of-sight restrictions; hence, some level of autonomy is required to make robotic inspection possible. In this work, a robotic solution to bridge bearing inspection is presented, and localisation methods are assessed as the first, and most, important step towards automation. Robot localisation is performed in both a lab environment and a real bridge bearing environment. In this paper, Adaptive Monte-Carlo Localisation is considered for localisation in a known map and gave comparable results to Hector-SLAM, with all results less than a defined error threshold of 10 cm. A combination of both of these methods are proposed to give a more robust approach that gives errors lower than the defined threshold in the real bridge. The experiments also show the need to provide an accurate starting point for each inspection within the bearing, for which we notionally suggest the use of a docking station that could also be used for improved autonomy, such as charging. In addition, proof-of-concept approaches for visual inspection tasks, such as geometry changes and foreign object detection are presented to show some of the proposed benefits of the system presented in this work.

Item Type:	Article
Additional Information:	publisher: Elsevier articletitle: Localisation of a mobile robot for bridge bearing inspection journaltitle: Automation in Construction articlelink: https://doi.org/10.1016/j.autcon.2018.07.003 content_type: article copyright: © 2018 The Authors. Published by Elsevier B.V.
Uncontrolled Keywords:	Bridge bearings, Robot, Inspection, Localisation
Depositing User:	Symplectic Admin
Date Deposited:	30 Aug 2018 06:13
Last Modified:	19 Jan 2023 01:25
DOI:	10.1016/j.autcon.2018.07.003
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3025701