MuJoCo Playground：ロボット学習のためのオープンソースフレームワーク
MuJoCo Playground
MJX上に構築された完全オープンソースのロボット学習フレームワークで、単一GPUで数分以内に方策を訓練でき、四足歩行・ヒューマノイド・多指ハンド・ロボットアームなど多様なプラットフォームでゼロショットsim-to-real転移を実現する。
著者: Kevin Zakka, Baruch Tabanpour, Qiayuan Liao, Mustafa Haiderbhai, Samuel Holt, Jing Yuan Luo, Arthur Allshire, Erik Frey, Koushil Sreenath, Lueder A. Kahrs, Carmelo Sferrazza, Yuval Tassa, Pieter Abbeel
分類: cs.RO
原文アブストラクト
We introduce MuJoCo Playground, a fully open-source framework for robot learning built with MJX, with the express goal of streamlining simulation, training, and sim-to-real transfer onto robots. With a simple "pip install playground", researchers can train policies in minutes on a single GPU. Playground supports diverse robotic platforms, including quadrupeds, humanoids, dexterous hands, and robotic arms, enabling zero-shot sim-to-real transfer from both state and pixel inputs. This is achieved through an integrated stack comprising a physics engine, batch renderer, and training environments. Along with video results, the entire framework is freely available at playground.mujoco.org
