While humanoid robots are becoming common in today’s world, quadruped robot dogs are taking over the operational sector for various businesses around the globe. Witnessing this demand, we have seen several companies like Boston Dynamics and Xiaomi come up with advanced robotic dogs that can perform heavy-duty tasks with ease. Now, ETH Zurich researchers have collaborated with popular GPU maker Nvidia to develop an advanced algorithm – to help train real-world robot dogs to walk and run on stable and unstable terrains.
Following the creation of the complex simulation using massively parallel deep reinforcement learning, the researchers used it to train the legs of real-world robots. This enabled the robots to learn to walk on slopes, stairs, and other complex terrains in minutes. Moreover, each time a robot dog learned to tackle challenging terrain, the researchers gave a more difficult terrain challenge to make the control algorithm more advanced.
