How artificial intelligence helps recycling become more circular


Smart robots, sensors and vision systems fortified with machine learning software are creeping into production at recycling facilities in Colorado, Japan and Europe.

The promise is twofold: Not only could these technologies help speed up the rate at which incoming items can be sorted, they could dramatically improve the accuracy with which operations can identify specific types of plastics and other materials — including one scourge of today’s system, items contaminated with food and other substances.

Two companies talking up the potential to make the act of processing everything from plastic to demolished construction materials far more efficient and scalable include five-year-old startup AMP Robotics, a machine learning and computer vision specialist headquartered in Louisville, Colorado. And a middle-aged Norwegian company, TOMRA, got its start managing reverse vending machines that uses sensors to endow its food sorting and recycling systems with more intelligence.

A new vision for sorting

As its name suggests, AMP Robotics’ innovations lie in how it’s rethinking recycling robots. Founder and CEO Matanya Horowitz began receiving grants back in 2014 to research and develop vision systems that could improve the accuracy of separating items with machines rather than by humans. The company’s equipment is “trained” by being shown millions of images — everything from logos to box shapes to dyed plastics.

“If you can teach a person to distinguish something, you can teach our vision system to distinguish it,” said Horowitz, speaking about this topic this week at Circularity 19. (…)

Heather Clancy

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