254 citations · 541 across the 10 of their papers we have counts for
3 papers · 1 filter
Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning
Nikita Rudin, David Hoeller, Philipp Reist +1
In this work, we present and study a training set-up that achieves fast policy generation for real-world robotic tasks by using massive parallelism on a single workstation GPU. We…
Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning
Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo +8
Isaac Gym offers a high performance learning platform to train policies for wide variety of robotics tasks directly on GPU. Both physics simulation and the neural network policy tr…
Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning
Nikita Rudin, Hendrik Kolvenbach, Vassilios Tsounis +1
In this article, we show that learned policies can be applied to solve legged locomotion control tasks with extensive flight phases, such as those encountered in space exploration.…