roboterax/humanoid-gym

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

2075 stars · 254 forks observed · 2026-08-28

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

Humanoid-Gym is a reinforcement learning framework built on Nvidia Isaac Gym for training locomotion skills in humanoid robots, with emphasis on zero-shot sim-to-real transfer. It includes a sim-to-sim pipeline to Mujoco for validating trained policies across different physics simulators.

Use cases

• train humanoid robot walking policies with reinforcement learning
• transfer RL locomotion policies from simulation to real robots
• validate trained policies in Mujoco before real-world deployment
• train locomotion for stairs, slopes, and uneven terrain
• adapt the framework to a custom humanoid robot

When to choose

• you are training locomotion skills for a humanoid robot
• you need zero-shot sim-to-real transfer of RL policies
• you want a sim-to-sim verification pipeline between Isaac Gym and Mujoco

When to avoid

• you need manipulation or dexterous hand training, which is still under development
• you lack a GPU capable of running Isaac Gym
• you work with non-humanoid robots requiring substantial rework

Facets

framework · maturity active

reinforcement-learning simulation robotics robotics reinforcement-learning machine-learning simulation python humanoid-robots sim2real sim2sim isaac-gym mujoco locomotion linux gpu

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markdown · JSON · MCP: product_card(name="roboterax/humanoid-gym")