Mountains of trash await the efforts of patient, artificial intelligence-enhanced robots; recycling plastic is just the beginning.
But to really unleash the power of AI on the recycling process, we need to rethink the entire sorting process. Today, recycling operations typically whittle down the mixed stream of materials to the target material by removing nontarget material—they do a “negative sort,” in other words. Instead, using AI vision systems with robotic pickers, we can perform a “positive sort.” Instead of removing nontarget material, we identify each object in a stream and select the target material.
To be sure, our recovery rate and purity are only as good as our algorithms. Those numbers continue to improve as our systems gain more experience in the world and our training data set continues to grow. We expect to eventually hit purity and recovery rates of 100 percent.
The implications of moving from more mechanical systems to AI are profound. Rather than coarsely sorting to 80 percent purity and then manually cleaning up the stream to 95 percent purity, a facility can reach the target purity on the first pass. And instead of having a unique sorting mechanism handling each type of material, a sorting machine can change targets just by a switch in algorithm.
"Robots pick up the garbage and junk and load it in there," he said. "Then they press one of these here thirteen buttons keying whatever they have dumped into one of the thirteen bins inside the truck. They're just plain lifting robots and not too brainy, but good enough to recognize most things they pick up.
(Read more about intelligent trash sorting by robots)
Scroll down for more stories in the same category. (Story submitted 6/28/2022)
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