Fanuc developed the revolutionary industrial robot to help countries like the United Kingdom achieve their recycling goals.
Fanuc developed in collaboration with Recycleye, a London-based tech start-up: The Recycleye Robotics Project. A robotic waste collection system powered by artificial intelligence
According to Recycleye spokesperson Ashika Patel, the machine can identify, sort and collect materials at a rate of 55 picks per minute, compared to 40 to 45 picks by humans.
According to Patel, “The cameras that Recycleye uses to recognize debris are similar to those found on the back of a normal phone. The computer can take around 60 images per second, and the images will be sent to the cloud, allowing us to provide the customer with useful and high-level information. Data such as pattern analysis and plant downtime can be sent to the customer. “
At a rate of 55 active picks per minute, Recycleye Robotics performs physical tasks such as fetching, picking up, and placing material. The innovative approach replaces manual processes with automation, allowing facilities to double their overall performance.
Recycleye Robotics was designed by Fanuc’s team of specialized automation engineers to be 75 percent lighter than any other robotic recycler currently on the market. Using the plug-and-play implementation eliminates the need for costly revisions.
Recycleye Robotics is powered by Recycleye Vision, a machine learning vision system. Where it constantly trains and identifies different objects, providing the robotic waste collection system to adapt to the changing flow process without having to manually renew it.
The mobile robotic collecting machine has already been installed on a number of plastic and paper sorting lines at two UK content recovery plants, and is expected to be deployed in France later this year. Around 700,000 robots have been deployed in various markets around the world.
The intelligent robotic system developed by Recycleye and Fanuc is ushering in a new era of economical and intelligent waste management automation.
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