机器人学
计算机科学
人工神经网络
寄主(生物学)
机器人
多样性(控制论)
人工智能
培训(气象学)
物理
生态学
气象学
生物
作者
Viktor Makoviychuk,Lukasz Wawrzyniak,Yunrong Guo,Michelle Lu,Kier Storey,Miles Macklin,David Hoeller,Nikita Rudin,Arthur Allshire,Ankur Handa,Gavriel State
标识
DOI:10.48550/arxiv.2108.10470
摘要
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 training reside on GPU and communicate by directly passing data from physics buffers to PyTorch tensors without ever going through any CPU bottlenecks. This leads to blazing fast training times for complex robotics tasks on a single GPU with 2-3 orders of magnitude improvements compared to conventional RL training that uses a CPU based simulator and GPU for neural networks. We host the results and videos at \url{https://sites.google.com/view/isaacgym-nvidia} and isaac gym can be downloaded at \url{https://developer.nvidia.com/isaac-gym}.
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