ProjectFeatured
acados
Fast and embedded solvers for nonlinear optimal control and MPC — used on real robots.
ProjectFeaturedAdvanced
CasADi
Symbolic framework for nonlinear optimization and algorithmic differentiation — backbone of many robot MPC stacks.
Why we recommend it
Foundational NLP / AD toolkit for robot control research. Latest stable release: 3.8.2 — https://github.com/casadi/casadi/releases/tag/3.8.2.
Overview
CasADi is a curated project on Embodied AI Hub.
Symbolic framework for nonlinear optimization and algorithmic differentiation — backbone of many robot MPC stacks.
Why it matters: Foundational NLP / AD toolkit for robot control research
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
- Symbolic framework for nonlinear optimization and algorithmic differentiation — backbone of many robot MPC stacks.
- Type: project; tags: 优化, 控制, 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
- 1Open the official URL and read the README / model card.
- 2Check license and citation requirements.
- 3Run the smallest official example before scaling.
- 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
Comments
Share an update or discuss CasADi.
Comments are public; please do not include private information.