Reinforcement Learning Bolsters Automated Detection of Concrete Cracks

Method could enable autonomous drones to monitor safety of bridges - Rust never sleeps, and cracking concrete doesn't get a day off either. The Jan. 28 collapse of Pittsburgh's Fern Hollow Bridge was a dramatic reminder of that fact. The exact cause of the collapse won't be known until the National Transportation Safety Board completes a months-long study, but Carnegie Mellon researchers have developed autonomous drone technology that someday might prevent similar catastrophes and lesser mishaps caused by deterioration. Working with Shimizu Corp., a Tokyo-based construction and civil engineering company, CMU's Robotics Institute built a prototype drone designed for monitoring bridges and other infrastructure. As part of that effort, researchers recently unveiled a new method that enables automated systems to more accurately detect and monitor cracks in reinforced concrete. Sebastian Scherer , an associate research professor of robotics and leader of the CMU team working with Shimizu, said the crack-detection method was one of several technologies that the university developed for the project, which concluded in February 2022.