# LeCAR-Lab/dial-mpc

Official implementation for the paper "Full-Order Sampling-Based MPC for Torque-Level Locomotion Control via Diffusion-Style Annealing". DIAL-MPC is a novel sampling-based MPC framework for legged robot full-order torque-level control with both precision and agility in a training-free manner.

Repository: https://github.com/LeCAR-Lab/dial-mpc
Canonical: https://ross.abutalabs.com/products/dial-mpc
Homepage: https://lecar-lab.github.io/dial-mpc/
Language: Python
License: Apache-2.0
License Family: permissive
Topics: diffusion, humanoid, legged-robots, mpc, online-control, optimal-control, quadruped, sampling-based-control
Last push: 2025-05-28T15:37:26+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 23, release rhythm 8, longevity 51
- inputs: {"age_days": 717, "days_push": 462, "days_rel": 665, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 997, forks 105 (observed 2026-09-03T02:15:06.498624+00:00)

## Summary
No AI-extracted summary yet.

## Member repositories
- LeCAR-Lab/dial-mpc (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-09-03T02:15:06.498624+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Data as of 2026-08-30T08:39:29.467469+00:00.