Ken Goldberg on Grasping and Picking Winners

05 Jul, 2021

Ken Goldberg on Grasping and Picking Winners

BCNM's Ken Goldberg and his work on grasping robotics was recently featured in COSMOS' The surprisingly complicated technology that goes into picking winners. In the article, Ken explains why picking isn't as easy as it seems and reveals how his team has attempted to address the difficulties behind robotic's infamous "picking problem".

From the article:

Can the robot work out a path through the branches to reach the apple? How hard does the robot need to pull to release the apple? Does it need to add a gentle twist to snap it off? And how much pressure should it apply? These complexities, Goldberg argues, place a robot apple picker toward the pinnacle of solutions of the picking problem, rather than a low-hanging fruit.

Goldberg and his graduate students recently revealed a solution that greatly speeds the training of picking robots: put the robot inside a simulation. Like some weird inversion of The Matrix, Goldberg’s research team sent their machines into the artificial world of Dex-Net 4.0, and, within that environment, where they controlled every element, they could run the robot through simulations far faster than would be possible in the real world. Ten thousand times faster. Mistakes that take hours or even days to learn to avoid in the real world could be overcome in minutes or seconds. And since every single object a robot has to pick has to be separately trained for, that big difference in training times quickly adds up.

Read the entire article here!