Researchers in California have built a DayDreamer robot that learned how to walk by itself in the real world not in a simulator

This is new research by the University of California Berkeley with Pieter Abbeel as lead author!

"Researchers at the University of California, Berkeley, have built a unique robot: one that taught itself how to walk. ..."

From the abstract:

"... The Dreamer algorithm has recently shown great promise for learning from small amounts of interaction by planning within a learned world model, outperforming pure reinforcement learning in video games. Learning a world model to predict the outcomes of potential actions enables planning in imagination, reducing the amount of trial and error needed in the real environment. However, it is unknown whether Dreamer can facilitate faster learning on physical robots. In this paper, we apply Dreamer to 4 robots to learn online and directly in the real world, without simulators. Dreamer trains a quadruped robot to roll off its back, stand up, and walk from scratch and without resets in only 1 hour. We then push the robot and find that Dreamer adapts within 10 minutes to withstand perturbations or quickly roll over and stand back up. On two different robotic arms, Dreamer learns to pick and place multiple objects directly from camera images and sparse rewards, approaching human performance. On a wheeled robot, Dreamer learns to navigate to a goal position purely from camera images, automatically resolving ambiguity about the robot orientation. Using the same hyperparameters across all experiments, we find that Dreamer is capable of online learning in the real world, establishing a strong baseline. ..."

Researchers in California have built a robot that learned how to walk by itself A small step for man, a great step for our future robot overlords.

DayDreamer: World Models for Physical Robot Learning