# robocasa/robocasa

RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots

Repository: https://github.com/robocasa/robocasa
Canonical: https://ross.abutalabs.com/products/robocasa
Homepage: https://robocasa.ai
Language: Python
License: NOASSERTION
License Family: other
Topics: humanoid-robot, physics-simulation, robot-learning, robotics
Last push: 2026-08-21T20:45:34+00:00

## Health v2 (maintenance only)
Score: 81/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 71, longevity 60
- inputs: {"age_days": 844, "days_push": 12, "days_rel": 196, "gap_med": 0, "n_releases_24m": 2}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1677, forks 243 (observed 2026-08-28T04:05:20.872373+00:00)

## What it is
RoboCasa is a large-scale simulation framework for training and benchmarking generally capable robots on everyday tasks, focused on kitchen environments. RoboCasa365 provides 365 tasks, 2,500+ kitchen scenes, thousands of 3D assets, 2,200+ hours of demonstration data, and benchmarking support for policy learning methods like Diffusion Policy, pi0, and GR00T.

## Use cases
- train robot policies on simulated everyday kitchen tasks
- benchmark imitation learning methods like diffusion policy
- generate synthetic robot demonstration trajectories
- evaluate generalist robot foundation models in sim
- collect human demonstrations via teleoperation
- hierarchical policy learning with subtask-annotated datasets

## When to choose
- you need large-scale simulated environments for robot manipulation research
- you want to benchmark policy learning methods like Diffusion Policy or GR00T
- you need demonstration datasets for training generalist robot policies
- you are researching multi-task or lifelong learning for robots

## When to avoid
- you need real-world robot hardware control
- you need non-kitchen or industrial simulation environments
- you want a lightweight simulator without large asset downloads

## Facets
- artifact type: library
- maturity: active
- function: simulation, machine-learning, benchmarking, data-generation
- domain: robotics, machine-learning, simulation, artificial-intelligence
- platform: python, cross-platform, windows
- tags: robot-learning, physics-simulation, humanoid-robot, imitation-learning, kitchen-tasks, demonstration-datasets, policy-learning, robosuite, linux, macos

## Member repositories
- robocasa/robocasa (main) score 81

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:20.872373+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:41:38.011767+00:00, confidence not recorded.
  - readme: https://github.com/robocasa/robocasa (fetched 2026-08-28T04:05:20.872373+00:00, sha ab55c5b55aac)
  - homepage: https://robocasa.ai (fetched 2026-08-29T11:15:04.208854+00:00, sha 178d02548524)
  - site_page: https://robocasa.ai/docs/build/html/introduction/overview.html (fetched 2026-08-29T11:15:04.218173+00:00, sha 9b7f3a4ef96b)
- Data as of 2026-08-30T08:39:29.467469+00:00.