Researchers at Carnegie Mellon University developed the In-the-Wild Human Imitating Robot Learning (WHIRL) algorithm to teach robots to perform tasks by observing people. WHIRL enables robots to gain knowledge from human-interaction videos and apply that data to new tasks, making them well-suited to learning household chores. The researchers outfitted a robot with a camera and the algorithm, and it learned to complete more than 20 tasks in natural environments.
In each case, the robot watched a human execute the task once, then practiced and learned to complete the task by itself. Instead of waiting for robots to be programmed or trained to successfully complete different tasks before deploying them into people's homes, this technology allows us to deploy the robots and have them learn how to complete tasks, all the while adapting to their environments and improving solely by watching.
More information: