Robot bridge inspector uses sensors and machine learning to hunt for defects


Autonomous bridge-inspecting robot could save lives by using smart sensors and machine learning algorithms to detect dangerous defects. Researchers at the University of Nevada have developed an autonomous robot, designed to inspect bridges and detect any structural damage before it can cause potential injury. The four-wheeled robot bridge inspector, called Seekur, uses a variety of tools to carry out its important task. These include ground-penetrating radar for looking beneath the surface of a bridge for underlying instabilities, sensors designed to search for possible corrosion of steel or cement, and a camera which analyzes cracks in the bridge's surface. A machine learning algorithm then analyzes all of this information and uses it to generate a color-coded map, which is passed on to (human) engineers to make them aware of weak spots.

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