May 1, 2020 (Tech Xplore) -- Researchers at Google Research and the University of California, Berkeley, have recently developed an imitation learning system that could enable a variety of agile locomotion behaviors in robots.
Their technique, presented in a paper pre-published on arXiv, allows robots to acquire new skills by imitating animals."This project builds on some previous works from computer graphics, which trained simulated characters to move by imitating human motion capture data," Jason Peng, one of the researchers who carried out the study, told TechXplore. "Most of these techniques were primarily applied in simulation, but in our recent project we took a first step towards applying them to real robots."
Peng and his colleagues initially trained a four-legged robot to imitate the movements and walking style of a dog within a simulated environment. Their system was trained on motion data recorded from a real dog, using an approach known as reinforcement learning.
"One of the advantages of training in simulation is that it is very fast, so we can simulate months of training in a matter of days," Peng explained. "Once the robot has been trained in simulation, we can adapt what it has learned to a real robot, using only a few minutes of data collected in the real world."