Thanks to artificial intelligence, a pair of robot legs was taught how to walk on their own. Well, to be specific, thanks to reinforcement learning (the training technique that teaches AIs complex behavior via trial and error), Cassie learned to walk from scratch. The robot legs are also capable of walking in a crouch and while carrying a load. Unlike the viral robots from Boston Dynamics, Cassie can’t dance, as MIT Technology Review details:
Reinforcement learning has been used to train bots to walk inside simulations before, but transferring that ability to the real world is hard. “Many of the videos that you see of virtual agents are not at all realistic,” says Chelsea Finn, an AI and robotics researcher at Stanford University, who was not involved in the work. Small differences between the simulated physical laws inside a virtual environment and the real physical laws outside it—such as how friction works between a robot’s feet and the ground—can lead to big failures when a robot tries to apply what it has learned. A heavy two-legged robot can lose balance and fall if its movements are even a tiny bit off.
The real Cassie was able to walk using the model learned in simulation without any extra fine-tuning. It could walk across rough and slippery terrain, carry unexpected loads, and recover from being pushed. During testing, Cassie also damaged two motors in its right leg but was able to adjust its movements to compensate. Finn thinks that this is exciting work. Edward Johns, who leads the Robot Learning Lab at Imperial College London agrees. “This is one of the most successful examples I have seen,” he says.
Image via MIT Technology Review