2016
Recurrent Neural Networks for driver activity anticipation via sensory-fusion architecture
ICRA 2016
Anticipating the future actions of a human is a widely studied problem in robotics that requires spatio-temporal reasoning. In this work we propose a deep learning approach for anticipation in sensory-rich robotics applications. We introduce a sensory-fusion architecture which jointly learns to anti