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acados

Fast and embedded solvers for nonlinear optimal control and MPC — used on real robots.

Official / sourceBack to Project
MPCControlOptimizationOpen source

Why we recommend it

Go-to open MPC / optimal-control stack for robots.6.0 — https://github.com/acados/acados/releases/tag/v0.6.0.6.0 — https://github.com/acados/acados/releases/tag/v0.6.0.6.0 — https://github.com/acados/acados/releases/tag/v0.6.0. Latest GitHub release: v0.6.0 — https://github.com/acados/acados/releases/tag/v0.6.0.

Overview

acados is a curated project on Embodied AI Hub.

Fast and embedded solvers for nonlinear optimal control and MPC — used on real robots.

Why it matters: Go-to open MPC / optimal-control stack for robots

Always verify install pins, licenses, and hardware requirements on the official site before production use.

Who it is for

Builders mapping open embodied stacks; researchers comparing SOTA baselines.

Key highlights

  • Fast and embedded solvers for nonlinear optimal control and MPC — used on real robots.
  • Type: project; tags: MPC, 控制, 优化, 开源
  • Hub recommended

When to use

  • You need this category of open resource in your stack map
  • You are shortlisting baselines before deep evaluation

When not to use

  • License or hardware constraints block adoption
  • You only need a closed commercial stack with vendor SLA

Getting started

  1. 1Open the official URL and read the README / model card.
  2. 2Check license and citation requirements.
  3. 3Run the smallest official example before scaling.
  4. 4Cross-link related hub resources for a full pipeline.

Caveats & pitfalls

  • Hub cards are curated summaries — verify upstream docs.
  • Stars and release names drift; treat metadata as approximate.

Content reviewed 2026-07-28