Rutgers Robot Leads Revolutionary Future of Bridge Health Management

As long as traffic is flowing, the vast network of roadways and bridges connecting the U.S. is generally taken for granted by motorists.  However, for the agencies and individuals responsible for the highway system its care and maintenance is of critical interest.  So when a revolutionary new tool comes along that can diagnose and manage the health of bridges more efficiently and effectively, the Federal Highway Administration (FHWA) and others in the industry are taking notice.

Rutgers University’s Center for Advanced Infrastructure and Transportation (CAIT), one of 10 Tier I University Transportation Centers sanctioned and supported by the U.S. Department of Transportation, demonstrated its robotic system for condition assessment of concrete bridge decks for FHWA administrator, Victor Mendez, and other key personnel on a suburban bridge in Virginia in November of last year.  CAIT, along with partner Turner-Fairbank Highway Research Center, unveiled the latest and most advanced product to emerge from the FHWA Long-Term Bridge Performance (LTBP) Program, a joint initiative to understand and improve bridge health and implement advanced management systems.

This valuable new way of gathering and looking at data holds great benefits for state departments of transportation and other bridge owners who are committed to using data-driven decisions for better bridge management.  The system’s flexibility—its ability to present multiple types of data at varying levels of detail or look for a specific type of problem—means it can serve a broad range of needs.  Armed with data, bridge owners can make quantitatively informed decisions regarding near-term preservation, maintenance, and rehabilitation operations, as well as use the information for long-term planning and management.

In addition, the robot automates data collection and simultaneously deploys multiple nondestructive evaluation technologies such as high resolution imaging, electromagnetic, electrical, and acoustic tools capturing very consistent information much more quickly than in the past.

“Before the robot, we would need six or seven highly trained technicians out on this bridge doing scans with all the different tools,” explains Nenad Gucunski, director of CAIT’s Infrastructure Condition Monitoring Program and chair of the Department of Civil and Environmental Engineering at Rutgers.  “Now, in a single sweep and four times faster, the robot can gather all of this data and give us a picture of the external and internal deck condition.”

Perhaps the most revolutionary aspect of this robotic system is its enhanced data interpretation and visualization capabilities. Using the latest technology, the system is able to combine various data sets and render an almost instantaneous three-dimensional snapshot of bridge deck condition that is easy to interpret.

Getting this kind of “picture” of deck condition is invaluable to bridge owners as state DOTs report expenditures for preservation, maintenance, and rehabilitation of bridges and especially bridge decks as disproportionately higher than for other roadway assets.  According to Gucunski, this is not surprising in view of the fact that decks—which take the brunt of traffic loads, environmental exposure, deicing chemicals, etc.—deteriorate faster than other bridge components.

With a significant number of bridges in the United States now more than 40 years old, having the means to determine bridge conditions more quantitatively and quickly, with a high level of consistency and safety and minimal interruption to commerce and the public, is needed now more than ever. 

For Mendez, the bridge robot is game-changing technology that he believes is at the forefront of a new industry.  “I’m going to be testifying before Congress and I’m going to raise this as an example of the [innovative solutions] that we in transportation engineering are bringing to the table,” he said, commemorating the moment by asking everyone associated with the project to sign his hard hat.