The dream is robots that do not simply blindly follow orders, but learn and understand intuitively what to do. The reinforcement learning system for controlling an inverted pendulum.

The company has been using reinforcement learning to help fallen robots right themselves. Agility shut off Digit’s obstacle avoidance for the above video to force a fall.

Building AI-powered robots that can learn how to interact with the physical world will enhance all forms of repetitive work.

Researchers developed a novel learning-based method so robots on extraterrestrial bodies can make decisions on their own about where and how to scoop up terrain samples.

By watching their own motions with a camera, robots can teach themselves about the structure of their own bodies and how they move, a new study by researchers at Columbia Engineering now reveals ...

PITTSBURGH — The Robotics Institute at Carnegie Mellon University in Pittsburgh is pioneering the future of robotics with innovative learning techniques. "Similar to how you train a dog, so we ...

Despite decades of progress, most robots are still programmed for specific, repetitive tasks. They struggle with the unexpected and can't adapt to new situations without painstaking reprogramming. But ...

Purdue professor programs robots and AI to navigate the physical world more easily — partly by teaching robots to dance.

New work has enabled robots to learn household chores by watching videos of people performing everyday tasks in their homes. Vision-Robotics Bridge, or VRB for short, uses the concept of ...

Folding laundry, cooking shrimp, wiping surfaces, unloading shopping baskets—today’s AI-powered robots are learning to do tasks that for their predecessors would have been extremely difficult.