Supplementary video for the IROS 2023 paper
"Ungar – A C++ Framework for Real-Time OptimalControl Using Template Metaprogramming" by Flavio De Vincenti and Stelian Coros.
2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023): https://ieee-iros.org/

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.

Project website:
https://github.com/fdevinc/ungar

Computational Robotics Lab:
http://crl.ethz.ch
  / computationalr2