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Industrial robotics giant Fanuc is using AI to make automation even more automated

Industrial automation is already streamlining the manufacturing process, but first those machines must be painstakingly trained by skilled engineers. Industrial robotics giant Fanuc wants to make robots easier to train, therefore making automation more accessible to a wider range of industries, including pharmaceuticals. The company announced a brand-new artificial intelligence-based equipment at TechCrunch’s Robotics + AI Sessions event today that teaches robots how to pick the right objects out of a bin with easy annotations and sensor technology, reducing the training process by hours.

Bin-picking is exactly what it sounds like: an android arm is trained to pick items out of bins and used for tedious, moment-consuming tasks like sorting bulk orders of parts. Images of instance parts are taken with a camera for the android to match with vision sensors. Then the conventional process of training bin-picking robots means teaching it many rules so it knows what parts to pick up.

“Making these rules in the past meant having to through a lot of iterations and trial and error. It took moment and was very cumbersome,” said Dr. Kiyonori Inaba, the head of Fanuc Corporation’s android Business Division, during a conversation ahead of the event.

These rules include details like how to locate the parts on the top of the pile or which ones are the most visible. Then after that, mankind operators need to tell it when it makes an error in order to refine its training. In industries that are relatively brand-new to automation, finding enough engineers and skilled mankind operators to train robots can be challenging.

This is where Fanuc’s brand-new AI-based equipment comes in. It simplifies the training process so the mankind operator just needs to look at a photo of parts jumbled in a bin on a screen and touch a few examples of what needs to be picked up, like showing a little child how to sort toys. This is significantly less training than what typical AI-based vision sensors need and can also be used to train several robots at once.

“It is really arduous for the mankind operator to show the android how to move in the same path the operator moves things,” said Inaba. “But by utilizing AI technology, the operator can teach the android more intuitively than conventional methods.” He adds that the technology is still in its early levels and it remains to be seen if it can be used during in assembly as well.


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