Seong-Hoon Kee

Autonomous robotic system for bridge deck data collection and analysis

Bridge deck inspection is conducted to identify bridge condition deterioration and, thus, to facilitate implementation of appropriate maintenance or rehabilitation procedures. In this paper, we report the development of a robotic system for bridge deck data collection and analysis. The robotic system accurately localizes itself and autonomously maneuvers on the bridge deck to collect visual images and conduct nondestructive evaluation (NDE) measurements. The developed robotic system can reduce the cost and time of the bridge deck data collection. Crack detection and mapping algorithm to build the deck crack maps is presented in detail. The electrical resistivity (ER), impact-echo (IE) and ultrasonic surface waves (USW) data collected by the robot are analyzed to generate the corrosion, delamination and concrete elastic modulus maps of the deck. The presented robotic system has been successfully deployed to inspect numerous bridges.

Implementation of a Fully Autonomous Platform for Assessment of Concrete Bridge Decks RABIT

RABIT (Robotics Assisted Bridge Inspection Tool) provides rapid and automated condition assessment of concrete bridge decks using multiple nondestructive evaluation (NDE) technologies integrated into a robotic platform. In particular, the system is designed to characterize the three most common deterioration types in concrete bridge decks: rebar corrosion, delamination, and concrete degradation. For that purpose, the system uses four technologies: electrical resistivity (ER), impact echo (IE), ground-penetrating radar (GPR), and ultrasonic surface waves (USW). In addition, the RABIT has two cameras for high resolution bridge deck imaging to provide a permanent record of the visible deterioration and surface features. The autonomous data collection is complemented by an advanced data analysis, interpretation and visualization. Most of the data analysis is conducted in real or near real time. The results are presented in terms of condition maps and condition indices. The data visualization platform facilitates an intuitive 3-dimensional presentation of the main three deterioration types and deck surface features. The data collection, analysis, and results presentation by the RABIT system are described and illustrated.

Development of an autonomous bridge deck inspection robotic system

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 United States. 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 United States.

Visual and Acoustic Data Analysis for the Bridge Deck Inspection Robotic System

Abstract - Bridge deck inspection is essential task to monitor thehealth of the bridges. This paper reports the data collectionand analysis for bridge decks based on our novel roboticsystem which can autonomously and accurately navigateon the bridge. The developed robotic system can lessen thecost and time of the bridge deck data collection and risksof human inspections. The advanced software is developedto allow the robot to collect visual images and conductnondestructive evaluation (NDE) measurements. The imagestitching algorithm to build a whole bridge image fromindividual images is presented in detail. The impact-echo(IE) and ultrasonic surface waves (USW) data collected bythe robot are analyzed to generate the delamination andconcrete elastic modulus maps of the deck. Keywords - Mobile robotic systems, Bridge deck inspection, ImageStitching, Nondestructive evaluation. I. Introduction The condition of bridges is critical for the safetyof the traveling public and economic vitality of thecountry. There are many bridges through the U.S. that arestructurally deficient or functionally obsolete. Conditionmonitoring and timely implementation of maintenanceand rehabilitation procedures are needed to reduce futurecosts associated with bridge management. Applicationof nondestructive evaluation (NDE) technologies is oneof the effective ways to monitor and predict bridgedeterioration. A number of NDE technologies are cur-rently used in bridge deck evaluation, including impact-echo (IE), ground penetrating radar (GPR), electricalresistivity (ER), ultrasonic surface waves (USW) testing,visual inspection, etc. [5], [22]. For a comprehensive andaccurate condition assessment, data fusion of simultane-ous multiple NDE techniques and sensory measurementsis desirable. Automated multi-sensor NDE techniqueshave been proposed to meet the increasing demandsfor highly-efficient, cost-effective and safety-guaranteedinspection and evaluation [7].Automated technologies have gained much attentionfor bridge inspection, maintenance, and rehabilitation.Mobile robotic inspection and maintenance systems aredeveloped for vision based crack detection and main-tenance of highways and tunnels [18], [19], [23]. Arobotic system for underwater inspection of bridge piersis reported in [3]. An adaptive control algorithm for abridge-climbing robot is developed [15]. Additionally,robotic systems for steel structured bridges are developed[2], [16], [21]. In one case, a mobile manipulator is usedfor bridge crack inspection [20]. A bridge inspectionsystem that includes a specially designed car with arobotic mechanism and a control system for automaticcrack detection is reported in [11], [12], [17]. Similarsystems are reported in [13]–[15] for vision-based auto-matic crack detection and mapping and [24] to detectcracks on the bridge deck and tunnel. Edge/crack detec-tion algorithms such as Sobel and Laplacian operatorsare used.Difference to all of the above mentioned works, ourpaper focus on the bridge deck data analysis which iscollected by our novel robotic system integrated withadvanced NDE technologies. The developed data analy-sis algorithms allows the robot to build the entire bridgedeck image and the global mapping of delamination andelastic modulus of the bridge decks. These advanceddata analysis algorithms take into account the advantagesof the accurate robotic localization and navigation toprovide the high-efficient assessments of the bridgedecks.The paper is organized as follows. In the nextsection, we describe the robotic data collection sys-tem and coordinate transformation. In Section III wepresent the image stitching algorithm and bridge deckviewer/monitoring software. In Section IV, we presentThe 31st International Symposium on Automation and Robotics in Construction and Mining (ISARC 2014)

RABIT: implementation, performance validation and integration with other robotic platforms for improved management of bridge decks

Accurate condition assessment and monitoring of concrete bridge deck deterioration progression requires both use of multiple nondestructive evaluation (NDE) technologies and automation in data collection and analysis. RABIT (robotics assisted bridge inspection tool) for bridge decks enables fully autonomous data collection at rates three or more times higher than it is typically done by a team of five inspectors using manual NDE technologies. The system concentrates on the detection and characterization of three most common internal deterioration and damage types: rebar corrosion, delamination, and concrete degradation. For that purpose, RABIT implements four NDE technologies: electrical resistivity (ER), ground-penetrating radar (GPR), impact echo (IE) and ultrasonic surface waves (USW) method. High productivity and higher spatial data resolution are achieved through the use of large sensor arrays or multiple probes for the four NDE methods. RABIT surveys also complement visual inspection by collecting high resolution images of the deck surface, which can be used for crack mapping and documentation of deck spalling, previous repairs, etc. The NDE technologies are used in a complementary way to enhance the overall condition assessment, certainty regarding the detected deterioration and better identification of the primary cause of deterioration. RABIT’s components, operation, field implementation and validation, as well as future integration with a robotic platform for minimally invasive rehabilitation, are described.

Use of Surface Wave Measurements to Characterize Surface-Breaking Cracks in Concrete Bridge Decks:

The depths of surface-breaking cracks in concrete bridge decks are characterized through the use of an extended surface wave transmission (SWT) method. For practical applications to concrete plates, the authors propose a measurement model that includes an appropriate configuration of the source and receivers, as well as a transmission function for the given configuration. A three-dimensional finite element model was used to conduct a series of numerical simulations to obtain the transmission function. Afterward, a proposed model was applied to characterize surface-breaking cracks in simulated and actual reinforced concrete bridge decks. As demonstrated, the proposed method was effective at characterizing the depth of a surface-breaking crack in a concrete bridge deck with an average error of 10% to 15%. In addition, it was found that a fusion of the results from the SWT and the surface wave velocity measurement led to a more accurate estimation of crack depth.