Graduate students working with CITRIS researchers Pieter Abbeel and Sergey Levine have made major advances in realistic computer animation, using deep reinforcement learning to create a virtual stuntman that mimics natural motions.
UC Berkeley NewsCenter, April 4, 2018 – It’s still easy to tell computer-simulated motions from the real thing – on the big screen or in video games, simulated humans and animals often move clumsily, without the rhythm and fluidity of their real-world counterparts.
But that’s changing. University of California, Berkeley researchers have now made a major advance in realistic computer animation, using deep reinforcement learning to recreate natural motions, even for acrobatic feats like break dancing and martial arts. The simulated characters can also respond naturally to changes in the environment, such as recovering from tripping or being pelted by projectiles.
“This is actually a pretty big leap from what has been done with deep learning and animation. In the past, a lot of work has gone into simulating natural motions, but these physics-based methods tend to be very specialized; they’re not general methods that can handle a large variety of skills,” said UC Berkeley graduate student Xue Bin “Jason” Peng. Each activity or task typically requires its own custom-designed controller.
“We developed more capable agents that behave in a natural manner,” he said. “If you compare our results to motion-capture recorded from humans, we are getting to the point where it is pretty difficult to distinguish the two, to tell what is simulation and what is real. We’re moving toward a virtual stuntman.”
The work could also inspire the development of more dynamic motor skills for robots.
A paper describing the development has been conditionally accepted for presentation at the 2018 SIGGRAPH conference in August in Vancouver, Canada, and was posted online April 10. Peng’s colleagues in the Department of Electrical Engineering and Computer Sciences are professor Pieter Abbeel and assistant professor Sergey Levine, along with Michiel van de Panne of the University of British Columbia.