Robotics
Having a machine learning agent interact with its environment requires true unsupervised learning, skill acquisition, active learning, exploration and reinforcement, all ingredients of human learning that are still not well understood or exploited through the supervised approaches that dominate deep learning today.
Our goal is to improve robotics via machine learning, and improve machine learning via robotics. We foster close collaborations between machine learning researchers and roboticists to enable learning at scale on real and simulated robotic systems.
We're exploring how to teach robots transferrable skills, by learning in parallel across many manipulation arms in our one-of-a-kind lab purpose-built for machine learning research:
We're teaching robots to predict what happens when they move objects around, in order to learn about the world around them and make better, safer decisions without supervision. We're also bringing advances in deep learning to the exciting and demanding world of self-driving cars to improve their safety and reliability.
Representative publications by Google Brain team members
- Pedestrian Detection with a Large-Field-of-View Deep Network Anelia Angelova, Alex Krizhevsky, Vincent Vanhoucke. Proceedings of ICRA 2015 (15 citations)
- Real-Time Pedestrian Detection with Deep Network Cascades Anelia Angelova, Alex Krizhevsky, Vincent Vanhoucke, Abhijit Ogale, Dave Ferguson. In Proceedings of BMVC'15, 2015 (11 citations)
- Continuous Deep Q-Learning with Model-based Acceleration Shixiang Gu, Tim Lillicrap, Ilya Sutskever, Sergey Levine. ICML, 2016 (5 citations)
- MuProp: Unbiased Backpropagation For Stochastic Neural Networks Shixiang Gu, Sergey Levine, Ilya Sutskever, Andriy Mnih. ArXiv, 2016 (for NIPS 2016) (3 citations)
- Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection Sergey Levine, Peter Pastor, Alex Krizhevsky, Deirdre Quillen. ArXiv, 2016 (2 citations)
- Unsupervised Learning for Physical Interaction through Video Prediction Chelsea Finn, Ian Goodfellow and Sergey Levine. ArXiv, 2016 (for NIPS 2016) (1 citation)
Current Google Brain team members who work on this area
- Anelia Angelova
- Konstantinos Bousmalis
- Thomas Breuel
- Erwin Coumans
- James Davidson
- Laura Downs
- Dumitru Erhan
- Marek Fiser
- Anthony Francis
- Ethan Holly
- Julian Ibarz
- Alex Irpan
- Eric Jang
- Matthew Kelcey
- Kai Kohlhoff
- Alexander Krizhevsky
- Sergey Levine
- Ken Oslund
- Deirdre Quillen
- Pierre Sermanet
- Leo Shamis
- Vikas Sindhwani
- Vincent Vanhoucke
