35 citations · 140 across the 13 of their papers we have counts for
3 papers · 1 filter
MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale
Dmitry Kalashnikov, Jacob Varley, Yevgen Chebotar +5
General-purpose robotic systems must master a large repertoire of diverse skills to be useful in a range of daily tasks. While reinforcement learning provides a powerful framework…
The Distracting Control Suite -- A Challenging Benchmark for Reinforcement Learning from Pixels
Austin Stone, Oscar Ramirez, Kurt Konolige +1
Robots have to face challenging perceptual settings, including changes in viewpoint, lighting, and background. Current simulated reinforcement learning (RL) benchmarks such as DM C…
PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations
Rico Jonschkowski, Roland Hafner, Jonathan Scholz +1
We propose position-velocity encoders (PVEs) which learn---without supervision---to encode images to positions and velocities of task-relevant objects. PVEs encode a single image i…