Autonomous robotic system for high-efficiency non-destructive bridge deck inspection and evaluation

La, Hung Manh; Lim, Ronny Salim; Basily, Basily; Gucunski, Nenad; Yi, Jingang; Maher, Ali; Romero, Francisco A.; Parvardeh, Hooman

doi:10.1109/coase.2013.6653886

Cited by 42 publications

(34 citation statements)

References 13 publications

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“…Also, we will address the problem of degraded localization accuracy due to moving objects. One of the best solutions is using Extended Kalman Filter (EKF) to fuse various data from different sources such as Differential Global Positioning System (DGPS), Inertial Measurement Unit (IMU), and robot wheel encoders to output the accurate and smooth localization of the robot on the bridge [34], [33].…”

Section: Discussionmentioning

confidence: 99%

A Robotic Crack Inspection and Mapping System for Bridge Deck Maintenance

Lim

Sheng

2014

IEEE Trans. Automat. Sci. Eng.

166

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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.Note to Practitioners-This work addresses crack detection and mapping on a bridge deck using a robotic system. Several challenges including coordinate transformation, robot localization and complete coverage path planning for the proposed robot system are tackled. This paper focuses mainly on the overall framework for such a robotic inspection system, therefore some of the techniques for handling shadows, paints, patches on bridges are not addressed. In real-world applications, these issues should be carefully incorporated into the design of the image processing algorithm. Also, there may be vibration caused by the passing traffic, which should be dealt with as well. The positioning of the ROCIM system is critical to crack mapping, hence more accurate robot localization techniques fusing various sensors such as differential GPS, Inertial Measurement Unit (IMU), etc. should be developed. It is also worth noting that the depth and severity of the cracks can be measured by employing advanced nondestructive evaluation (NDE) sensors, such as impact echo and ultrasonic surface wave.

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Section: Discussionmentioning

confidence: 99%

A Robotic Crack Inspection and Mapping System for Bridge Deck Maintenance

Lim

Sheng

2014

IEEE Trans. Automat. Sci. Eng.

166

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“…The details of the system mechatronic design and the autonomous robotic localization algorithm based Extended Kalman Filter (EKF) are provided in Refs. , .…”

Section: The Robotic System For Bridge Deck Inspection and Evaluationmentioning

confidence: 99%

Development of an autonomous bridge deck inspection robotic system

Gucunski

Dana

et al. 2017

Journal of Field Robotics

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The threat to safety of aging bridges has been recognized as a critical concern to the general public due to the poor condition of many bridges in the U.S. Currently, the bridge inspection is conducted manually, and it is not efficient to identify bridge condition deterioration in order to facilitate implementation of appropriate maintenance or rehabilitation procedures. In this paper, we report a new development of the autonomous mobile robotic system for bridge deck inspection and evaluation. The robot is integrated with several nondestructive evaluation (NDE) sensors and a navigation control algorithm to allow it to accurately and autonomously maneuver on the bridge deck to collect visual images and conduct NDE measurements. The developed robotic system can reduce the cost and time of the bridge deck data collection and inspection. For efficient bridge deck monitoring, the crack detection algorithm to build the deck crack map is presented in detail. The impact-echo (IE), ultrasonic surface waves (USW) and electrical resistivity (ER) data collected by the robot are analyzed to generate the delamination, concrete elastic modulus, corrosion maps of the bridge deck, respectively. The presented robotic system has been successfully deployed to inspect numerous bridges in more than ten different states in the U.S.

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“…The robot autonomously maneuvers on the bridge based on the advanced localization and navigation algorithm reported in the previous works (La et al 2013b;Gucunski et al 2013;La et al 2013a).…”

Section: Data Collectionmentioning

confidence: 99%

Data analysis and visualization for the bridge deck inspection and evaluation robotic system

Gucunski

Kee

et al. 2015

Vis. in Eng.

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Background: Bridge deck inspection is essential task to monitor the health of the bridges. Condition monitoring and timely implementation of maintenance and rehabilitation procedures are needed to reduce future costs associated with bridge management. A number of Nondestructive Evaluation (NDE) technologies are currently used in bridge deck inspection and evaluation, including impact-echo (IE), ground penetrating radar (GPR), electrical resistivity (ER), ultrasonic surface waves (USW) testing, and visual inspection. However, current NDE data collection is manually conducted and thus faces with several problems such as prone to human errors, safety risks due to open traffic, and high cost process. Methods: This paper reports the automated data collection and analysis for bridge decks based on our novel robotic system which can autonomously and accurately navigate on the bridge. The developed robotic system can lessen the cost and time of the bridge deck data collection and risks of human inspections. The advanced software is developed to allow the robot to collect visual images and conduct NDE measurements. The image stitching algorithm to build a whole bridge deck image from individual images is presented in detail. The ER, IE and USW data collected by the robot are analyzed to generate the corrosion, delamination and concrete elastic modulus maps of the deck, respectively. These condition maps provide detail information of the bridge deck quality. Conclusions:The automated bridge deck data collection and analysis is developed. The image stitching algorithm allowed to generate a very high resolution image of the whole bridge deck, and the bridge viewer software allows to calibrate the stitched image to the bridge coordinate. The corrosion, delamination and elastic modulus maps were built based on ER, IE and USW data collected by the robot to provide easy evaluation and condition monitoring of bridge decks.

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Autonomous robotic system for high-efficiency non-destructive bridge deck inspection and evaluation

Cited by 42 publications

References 13 publications

A Robotic Crack Inspection and Mapping System for Bridge Deck Maintenance

A Robotic Crack Inspection and Mapping System for Bridge Deck Maintenance

Development of an autonomous bridge deck inspection robotic system

Data analysis and visualization for the bridge deck inspection and evaluation robotic system

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