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OpEn: Code Generation for Embedded Nonconvex Optimization
Open accessAbstract
We present Optimization Engine (OpEn): an open-source code generation framework for real-time embedded nonconvex optimization, which implements a novel numerical method. OpEn combines the proximal averaged Newton-type method for optimal control (PANOC) with the penalty and augmented Lagrangian methods to compute approximate stationary points of nonconvex problems. The proposed method involves very simple algebraic operations such as vector products, has a low memory footprint and exhibits very good convergence properties that allow the solution of nonconvex problems on embedded devices. OpEn’s core solver is written is Rust — a modern, high-performance, memory-safe and thread-safe systems programming language — while users can call it from Python, MATLAB, C, C++, ROS or over a TCP socket.
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“Such single control layer architectures with perception and actuation constraints have been investigated also in [5], [6].”
From A Perception-Aware NMPC for Vision-Based Target Tracking and Collision Avoidance with a Multi-Rotor UAV (2022) · cites this paper as [6]
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“However, collision avoidance tasks with respect to (w.r.t.) multiple dynamic obstacles are not explicitly taken into account.”
From A Perception-Aware NMPC for Vision-Based Target Tracking and Collision Avoidance with a Multi-Rotor UAV (2022) · cites this paper as [6]
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“In these works, the authors make use of generic dynamic models which can represent a large class of multirotor UAVs [18]. This allows to formulate the problem for both standard coplanar under-actuated vehicles as well as for fully-actuated platforms with tilted propellers characterized by a fixed geometry (i.e., propellers' orientation is fixed).”
From A Perception-Aware NMPC for Vision-Based Target Tracking and Collision Avoidance with a Multi-Rotor UAV (2022) · cites this paper as [6]
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Research works printed but not linked: 20
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Cited by
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Dmytruk, A., Silano, G., Bicego, D., Licea, D. B., & Saska, M. (2022) · 2022 International Conference on Unmanned Aircraft Systems (ICUAS) · doi:10.1109/icuas54217.2022.9836071 · Cited by 8
Metadata
- Authors
- Sopasakis, P., Fresk, E., & Patrinos, P.
- Affiliations
- Queen's University Belfast (GB)
- KU Leuven (BE)
- Corresponding author
- Sopasakis, Pantelis
- Venue
- IFAC-PapersOnLine
- Publisher
- Elsevier BV
- Published
- 2020
- Volume
- 53
- Issue
- 2
- Pages
- 6548-6554
- ISSN
- 2405-8963 (ISSN-L)
- OpenAlex
- W3007532216
- Cited by
- 91
- References
- 0
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 14 · 2023: 23 · 2022: 23 · 2021: 8 · 2020: 8
- FWCI
- 7.67
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- IFAC-PapersOnLine (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Lirias (submittedVersion, cc-by-nc-nd)
- Research Portal (Queen's University Belfast) (submittedVersion, cc-by-nc-nd)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
- Physical Sciences › Mathematics › Numerical Analysis › Advanced Optimization Algorithms Research
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Optimization and Variational Analysis
- Keywords
- open, embedded optimization, non-convex optimization, code generation, optimal control, penalty method, augmented Lagrangian method, critical points, real-time embedded systems, Rust, open-source solver
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