Home Machine Control & Robotics First autonomous vehicle for pothole repair

First autonomous vehicle for pothole repair

by Charles Choi
An artist impression of the Robotiz3d autonomous robot. Courtesy: Robotiz3d.

A British startup, Robotiz3d, has developed what it suggests may be the world’s first set of autonomous vehicles that use artificial intelligence to locate and fix cracks and potholes in roads, the company announced in November.

Robotiz3d noted that potholes currently cost U.S. drivers $26 billion each year and U.K. drivers £1.7 billion annually. This problem is only expected to get worse, given aging infrastructure, increasing road use and extreme weather conditions.

Based initially on patented research developed at the University of Liverpool in England, the new autonomous robots can analyze the geometry of road defects to assess their size. They then use a unique artificial intelligence prediction algorithm to help enable local authorities to predict road conditions accurately and prioritize preventative road maintenance. They can also seal the defects before they get worse.

Robotiz3d said its autonomous vehicles can gather data while traveling up to 60 miles per hour. They scan one lane at a time with a field of view up to 3 meters, and can be used day and night in all weather conditions.

When compared with conventional road maintenance techniques, the startup claims that its new efficient electric autonomous vehicles can lead to 90 percent cost savings, 70 percent faster repair times, and three times less carbon dioxide emissions. The company, located at Daresbury Laboratory in Liverpool, said it is now testing their prototypes and making substantial progress towards commercializing its technology.

“This is the first autonomous technology of this kind developed specifically to tackle the pothole crisis which plagues many parts of the country, and which is estimated to have cost more than £1 billion to repair over the last decade,” Lisa Layzell, CEO and co-founder at Robotiz3d, said in a statement.

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