2019
State Representation Learning with Robotic Priors for Partially Observable Environments
IROS 2019poster
We introduce Recurrent State Representation Learning (RSRL) to tackle the problem of state representation learning in robotics for partially observable environments. To learn low-dimensional state representations, we combine a Long Short Term Memory network with robotic priors. RSRL introduces new p…