1k citations · 3.7k across the 13 of their papers we have counts for
4 papers · 1 filter
Domain Randomization and Generative Models for Robotic Grasping
Joshua Tobin, Lukas Biewald, Rocky Duan +8
Deep learning-based robotic grasping has made significant progress thanks to algorithmic improvements and increased data availability. However, state-of-the-art models are often tr…
Hindsight Experience Replay
Marcin Andrychowicz, Filip Wolski, Alex Ray +7
Dealing with sparse rewards is one of the biggest challenges in Reinforcement Learning (RL). We present a novel technique called Hindsight Experience Replay which allows sample-eff…
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World
Josh Tobin, Rachel Fong, Alex Ray +3
Bridging the 'reality gap' that separates simulated robotics from experiments on hardware could accelerate robotic research through improved data availability. This paper explores…
One-Shot Imitation Learning
Yan Duan, Marcin Andrychowicz, Bradly C. Stadie +5
Imitation learning has been commonly applied to solve different tasks in isolation. This usually requires either careful feature engineering, or a significant number of samples. Th…