Researchers Develop Robot That Learns By Itself Through Trial and Error, Like Humans

Researchers have developed algorithms that enable robots to learn motor tasks through trial and error, like humans.

The technology was demonstrated recently in which robot was assigned to complete various tasks, i.e., putting a clothes hanger on a rack, assembling a toy plane, screwing a cap on a water bottle, and more, without pre-programmed details about its surroundings.

"What we're reporting on here is a new approach to empowering a robot to learn," said Pieter Abbeel.

"The challenge of putting robots into real-life settings, like homes or offices, is that those environments are constantly changing. The robot must be able to perceive and adapt to its surroundings," added co-researcher Trevor Darrell.

Researchers noted that the algorithm leverages a new branch of artificial intelligence knowns as deep learning.

Researchers worked with a Willow Garage Personal Robot 2 (PR2), nicknamed BRETT.

The findings of the experiment will be presented at the International Conference on Robotics and Automation (ICRA) in Seattle on May 28