UC Berkeley: Deep Learning Helps Robots Grasp And Move Objects With Ease

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UC Berkeley engineers have created new software that combines neural networks with motion planning software to give robots the speed and skill to assist in warehouse environments. (UC Berkeley video courtesy Ken Goldberg lab)

In the past year, lockdowns and other COVID-19 safety measures have made online shopping more popular than ever, but the skyrocketing demand is leaving many retailers struggling to fulfill orders while ensuring the safety of their warehouse employees.
Researchers at the University of California, Berkeley, have created new artificial intelligence software that gives robots the speed and skill to grasp and smoothly move objects, making it feasible for them to soon assist humans in warehouse environments. The technology is described in a paper published online today (Wednesday, Nov. 18) in the journal Science Robotics.
Automating warehouse tasks can be challenging because many actions that come naturally to humans — like deciding where and how to pick up different types of objects and then coordinating the shoulder, arm and wrist movements needed to move each object from one location to another — are actually quite difficult for robots. Robotic motion also tends to be jerky, which can increase the risk of damaging both the products and the robots.
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