# leggedrobotics/legged_gym

Isaac Gym Environments for Legged Robots

Repository: https://github.com/leggedrobotics/legged_gym
Canonical: https://ross.abutalabs.com/products/legged_gym
Language: Python
License: NOASSERTION
License Family: other
Last push: 2025-05-29T08:02:13+00:00

## Health v2 (maintenance only)
Score: 43/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 24, release rhythm 35, longevity 100
- inputs: {"age_days": 1780, "days_push": 461, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3102, forks 584 (observed 2026-08-28T04:07:43.642131+00:00)

## What it is
A Python library providing Isaac Gym environments for training legged robots (e.g., ANYmal) to walk on rough terrain with reinforcement learning. It includes sim-to-real transfer components such as actuator networks, domain randomization, noisy observations, and random pushes during training.

## Use cases
- train a quadruped robot to walk on rough terrain with reinforcement learning
- run PPO training for legged locomotion in Isaac Gym
- set up sim-to-real transfer with friction and mass randomization
- create custom robot environments by extending the legged robot config classes
- reproduce the ANYmal rough-terrain locomotion results from the paper

## When to choose
- you want to train legged robot locomotion policies with NVIDIA Isaac Gym
- you need a proven sim-to-real pipeline for quadruped robots
- you want a configurable, inheritance-based RL environment framework for robotics research

## When to avoid
- you are starting a new project - the maintainers recommend migrating to Isaac Lab
- you need a simulator other than Isaac Gym
- you require long-term support or frequent updates, as the repo receives limited maintenance

## Facets
- artifact type: library
- maturity: maintenance
- function: reinforcement-learning, simulation, machine-learning, robotics
- domain: robotics, reinforcement-learning, simulation, machine-learning
- platform: python
- tags: isaac-gym, legged-robots, sim-to-real, locomotion, ppo, anymal, robot-learning, linux, gpu

## Member repositories
- leggedrobotics/legged_gym (main) score 43

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:43.642131+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 2026-08-29T18:46:20.892590+00:00, confidence not recorded.
  - readme: https://github.com/leggedrobotics/legged_gym (fetched 2026-08-28T04:07:43.642131+00:00, sha 292bda5928e8)
- Data as of 2026-08-30T08:39:29.467469+00:00.