# silvery107/rl-mpc-locomotion

Deep RL for MPC control of Quadruped Robot Locomotion

Repository: https://github.com/silvery107/rl-mpc-locomotion
Canonical: https://ross.abutalabs.com/products/rl-mpc-locomotion
Homepage: https://docs.google.com/presentation/d/18bznpYrkCPnhCisySPDz18hvL3Ytere7JiJEbdLvpgU/edit?usp=sharing
Language: Python
License: MIT
License Family: permissive
Topics: quadruped, isaac-gym, mpc, reinforcement-learning, robotics
Last push: 2026-04-26T06:10:10+00:00

## Health v2 (maintenance only)
Score: 68/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 79, release rhythm 35, longevity 100
- inputs: {"age_days": 1745, "days_push": 129, "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 1020, forks 92 (observed 2026-08-28T04:03:15.160774+00:00)

## What it is
A Python framework combining deep reinforcement learning with model predictive control (MPC) for quadruped robot locomotion, where a policy network dynamically predicts MPC weight parameters. It supports Unitree Go1, A1, and Aliengo robots with parallel training in NVIDIA Isaac Gym.

## Use cases
- train RL policies for quadruped locomotion
- simulate and control a quadruped robot with MPC
- run a hierarchical RL+MPC controller on a Unitree robot
- learn gait control for legged robots in Isaac Gym
- port an MPC locomotion controller between simulators

## When to choose
- you need RL-trained MPC weight prediction for quadruped locomotion
- you work with Unitree A1, Go1, or Aliengo robots
- you want a Python MPC controller with open sensor/motor interfaces
- you need fast parallel RL training in Isaac Gym

## When to avoid
- you need out-of-the-box sim2real deployment (not included)
- you work with biped or non-quadruped robots
- you need a non-Python MPC implementation
- you cannot use NVIDIA Isaac Gym or CUDA GPUs

## Facets
- artifact type: library
- maturity: active
- function: reinforcement-learning, simulation, robotics, machine-learning
- domain: robotics, reinforcement-learning, machine-learning, simulation
- platform: python
- tags: quadruped, mpc, isaac-gym, sim2real, locomotion, unitree, pytorch, linux, gpu

## Member repositories
- silvery107/rl-mpc-locomotion (main) score 68

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:15.160774+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 2026-08-30T07:09:19.505599+00:00, confidence not recorded.
  - readme: https://github.com/silvery107/rl-mpc-locomotion (fetched 2026-08-28T04:03:15.160774+00:00, sha c4f808f6ed31)
  - homepage: https://docs.google.com/presentation/d/18bznpYrkCPnhCisySPDz18hvL3Ytere7JiJEbdLvpgU/edit?usp=sharing (fetched 2026-08-29T13:09:30.563681+00:00, sha cccc4b45b808)
- Data as of 2026-08-30T08:39:29.467469+00:00.