Ungar - A C++ Framework for Real-Time Optimal Control Using Template Metaprogramming
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Author / Producer
Date
2023
Publication Type
Conference Paper
ETH Bibliography
yes
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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.
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Publication status
published
Editor
Book title
2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Journal / series
Volume
Pages / Article No.
6297 - 6303
Publisher
IEEE
Event
36th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Organisational unit
09620 - Coros, Stelian / Coros, Stelian
02284 - NFS Digitale Fabrikation / NCCR Digital Fabrication
Notes
Funding
200644 - Fabrication-oriented Design of Nonlinear Network Materials (SNF)
866480 - Computational Models of Motion for Fabrication-aware design of Bioinspired Systems (EC)
866480 - Computational Models of Motion for Fabrication-aware design of Bioinspired Systems (EC)