Interlocking AIs let robots pick and place faster than ever

One of the jobs for which robots are best suited is the tedious, repetitive “pick and place” task common in warehouses — but humans are still much better at it. UC Berkeley researchers are picking up the pace with a pair of machine learning models that work together to let a robot arm plan its grasp and path in just milliseconds.

People don’t have to think hard about how to pick up an object and put it down somewhere else — it’s not only something we’ve had years of practice doing every day, but our senses and brains are well adapted for the task. No one thinks, “what if I picked up the cup, then jerked it really far up and then sideways, then really slowly down onto the table” — the paths we might move an object along are limited and usually pretty…

Read Story

Related Post