Ungar -- A C++ Framework for Real-Time Optimal Control Using Template Metaprogramming

TL;DR

Ungar is a C++ library leveraging template metaprogramming to efficiently solve high-dimensional optimal control problems, demonstrated in robotics applications like quadruped locomotion and loco-manipulation.

Contribution

It introduces a flexible, high-performance C++ framework for modeling and solving complex optimal control problems using compile-time techniques.

Findings

Achieves high runtime efficiency for complex OCPs

Supports expressive formulations of structured dynamical systems

Successfully applied to robotics control tasks

Abstract

We present Ungar, an open-source library to aid the implementation of high-dimensional optimal control problems (OCPs). We adopt modern template metaprogramming techniques to enable the compile-time modeling of complex systems while retaining maximum runtime efficiency. Our framework provides syntactic sugar to allow for expressive formulations of a rich set of structured dynamical systems. While the core modules depend only on the header-only Eigen and Boost.Hana libraries, we bundle our codebase with optional packages and custom wrappers for automatic differentiation, code generation, and nonlinear programming. Finally, we demonstrate the versatility of Ungar in various model predictive control applications, namely, four-legged locomotion and collaborative loco-manipulation with multiple one-armed quadruped robots. Ungar is available under the Apache License 2.0 at https://github.com/fdevinc/ungar.