# real-stanford/universal_manipulation_interface

Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots

Repository: https://github.com/real-stanford/universal_manipulation_interface
Canonical: https://ross.abutalabs.com/products/universal_manipulation_interface
Homepage: https://umi-gripper.github.io/
Language: Python
License: MIT
License Family: permissive
Last push: 2026-05-26T17:22:25+00:00

## Health v2 (maintenance only)
Score: 63/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 84, release rhythm 35, longevity 66
- inputs: {"age_days": 929, "days_push": 99, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1560, forks 285 (observed 2026-08-28T04:05:03.727655+00:00)

## What it is
Universal Manipulation Interface (UMI) is a data collection and policy learning framework that transfers in-the-wild human demonstrations into deployable robot manipulation policies using handheld grippers. It includes a SLAM pipeline for processing demonstrations and a policy interface with latency matching and relative-trajectory action representation for hardware-agnostic deployment.

## Use cases
- collect robot manipulation demonstrations with handheld grippers
- train robot policies from human demonstrations
- run SLAM on gripper-mounted camera footage
- deploy manipulation policies across different robot hardware
- learn bimanual and dynamic manipulation skills
- zero-shot generalize manipulation policies to new environments

## When to choose
- you need low-cost portable robot demonstration data collection without a robot
- you want hardware-agnostic manipulation policies trained on human demos
- you need bimanual, precise, or long-horizon manipulation capabilities

## When to avoid
- you need a general-purpose robotics simulator
- you work outside Ubuntu 22.04 and cannot use Docker
- you need locomotion or mobile navigation rather than manipulation

## Facets
- artifact type: framework
- maturity: active
- function: machine-learning, robotics, computer-vision, data-science
- domain: robotics, machine-learning, artificial-intelligence
- platform: python
- tags: robot-manipulation, imitation-learning, slam, handheld-gripper, policy-learning, demonstration-collection, linux, docker

## Member repositories
- real-stanford/universal_manipulation_interface (main) score 63

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:03.727655+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 2026-08-30T04:29:47.749495+00:00, confidence not recorded.
  - readme: https://github.com/real-stanford/universal_manipulation_interface (fetched 2026-08-28T04:05:03.727655+00:00, sha 67b517e55db0)
  - homepage: https://umi-gripper.github.io/ (fetched 2026-08-29T11:29:32.547664+00:00, sha fc71408bccc9)
- Data as of 2026-08-30T08:39:29.467469+00:00.