DocumentCode :
54280
Title :
A Robotic Crack Inspection and Mapping System for Bridge Deck Maintenance
Author :
Lim, Ronny Salim ; Hung Manh La ; Weihua Sheng
Author_Institution :
Center for Adv. Infrastruct. & Transp., Rutgers Univ., Piscataway, NJ, USA
Volume :
11
Issue :
2
fYear :
2014
fDate :
Apr-14
Firstpage :
367
Lastpage :
378
Abstract :
One of the important tasks for bridge maintenance is bridge deck crack inspection. Traditionally, a human inspector detects cracks using his/her eyes and marks the location of cracks manually. However, the accuracy of the inspection result is low due to the subjective nature of human judgement. We propose a crack inspection system that uses a camera-equipped mobile robot to collect images on the bridge deck. In this method, the Laplacian of Gaussian (LoG) algorithm is used to detect cracks and a global crack map is obtained through camera calibration and robot localization. To ensure that the robot collects all the images on the bridge deck, a path planning algorithm based on the genetic algorithm is developed. The path planning algorithm finds a solution which minimizes the number of turns and the traveling distance. We validate our proposed system through both simulations and experiments.
Keywords :
Gaussian processes; bridges (structures); condition monitoring; crack detection; genetic algorithms; industrial robots; inspection; maintenance engineering; mechanical engineering computing; mobile robots; object detection; path planning; robot vision; Laplacian of Gaussian; LoG algorithm; bridge deck crack inspection; bridge deck maintenance; camera calibration; camera-equipped mobile robot; crack detection; genetic algorithm; global crack map; mapping system; path planning algorithm; robot localization; robotic crack inspection; Bridges; Cameras; Inspection; Mobile robots; Robot kinematics; Robot vision systems; Crack inspection; mobile robot; path planning;
fLanguage :
English
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1545-5955
Type :
jour
DOI :
10.1109/TASE.2013.2294687
Filename :
6705706
Link To Document :
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