TinyMPC/TinyMPC

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1081 stars · 131 forks observed · 2026-09-03

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

TinyMPC is an open-source C++ solver for convex model-predictive control with a small memory footprint, designed for resource-constrained microcontrollers and robotics. It uses an ADMM-based algorithm, supports state/input bounds and second-order cone constraints, and offers Python, Julia, and MATLAB interfaces for code generation.

Use cases

• run model-predictive control on a microcontroller
• control a quadrotor with MPC
• generate embedded C++ code for a controller
• implement obstacle avoidance on resource-constrained robots
• compare MPC solver performance on MCUs
• recover a drone from extreme poses

When to choose

• you need fast MPC with a tiny memory footprint on embedded hardware
• you're building control for small robots like the Crazyflie
• you want code generation from Python/MATLAB/Julia to C++

When to avoid

• you need large-scale or nonconvex MPC on desktop/server hardware
• you want a batteries-included robotics framework rather than a solver
• you need a solver with extensive third-party integrations out of the box

Facets

library · maturity active

simulation embedded math sdk robotics embedded-systems autonomous-vehicles cpp embedded python cross-platform model-predictive-control admm control-solver microcontroller code-generation quadrotor convex-optimization algorithms linux

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