ARISE-Initiative/robomimic

Health v2 · maintenance only

Adoption not part of the score

1535 stars · 416 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

robomimic is a modular Python framework for robot learning from demonstration, providing standardized demonstration datasets and offline learning algorithms for robot manipulation. It enables researchers to fairly benchmark tasks and algorithms in a reproducible way.

Use cases

• train robot manipulation policies from human demonstrations
• benchmark imitation learning algorithms on standardized datasets
• run offline reinforcement learning experiments like IQL
• train diffusion policy models for robot control
• evaluate language-conditioned robot policies
• reproduce robot learning research results

When to choose

• you need a reproducible benchmark suite for robot learning from demonstration
• you want ready-made manipulation datasets and offline RL algorithms
• you work with robosuite or MuJoCo simulation environments

When to avoid

• you need real-time online RL training with live robot interaction
• you want a general-purpose deep learning framework unrelated to robotics
• you need plug-and-play deployment on physical robots without research setup

Facets

framework · maturity active

machine-learning deep-learning simulation benchmarking robotics machine-learning artificial-intelligence python robot-learning imitation-learning offline-rl learning-from-demonstration manipulation robosuite diffusion-policy research linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="ARISE-Initiative/robomimic")