Daniel Menges
Om
Daniel Menges is a Ph.D. candidate at the Norwegian University of Science and Technology. He is part of the SFI AutoShip project, where his research field is related to Situational Awareness of Autonomous Ships. Furthermore, he is part of the PERSEUS doctoral program approaching the topical area of Digital Twins.
He holds a Master's Degree in Mechanical Engineering from the Karlsruhe Institute of Technology in Germany, where he specialized in Automation and Robotics and focused on the fields of Cybernetics and Control Theory.
Forskning
Objectives:
- Developing algorithms for improving the situational awareness of autonomous surface vessels
- Developing a digital twin of an autonomous surface vessel and its environment
This PhD project aims to improve the situational awareness of autonomous vessels. Autonomous sea operations depend on a reliable perception of the environment and a sophisticated situational awareness of the ship’s conditions. The enhanced perception can supply controllers with extended information to improve the overall decision-making process. Key enablers for testing such modern algorithms in a safe environment are digital twins. Digital twins allow the simulation of several events, including critical collision avoidance scenarios. For this purpose, a well-developed digital twin has to map reality with precise models and real-time data streams.
Publikasjoner
2024
-
Menges, Daniel;
Von Brandis, Andreas;
Rasheed, Adil.
(2024)
Digital Twin of Autonomous Surface Vessels for Safe Maritime Navigation Enabled through Predictive Modeling and Reinforcement Learning.
arXiv.org
Vitenskapelig artikkel
-
Menges, Daniel;
Rasheed, Adil.
(2024)
Computationally and Memory-Efficient Robust Predictive Analytics Using Big Data.
arXiv.org
Vitenskapelig artikkel
-
Menges, Daniel;
Tengesdal, Trym;
Rasheed, Adil.
(2024)
Nonlinear Model Predictive Control for Enhanced Navigation of Autonomous Surface Vessels.
arXiv.org
Vitenskapelig artikkel
-
Vaaler, Aksel;
Husa, Svein Jostein;
Menges, Daniel;
Larsen, Thomas Nakken;
Rasheed, Adil.
(2024)
Modular Control Architecture for Safe Marine Navigation: Reinforcement Learning and Predictive Safety Filters.
arXiv.org
Vitenskapelig artikkel
2023
-
Menges, Daniel;
Rasheed, Adil.
(2023)
An environmental disturbance observer framework for autonomous surface vessels.
Ocean Engineering
Vitenskapelig artikkel
-
Menges, Daniel;
Sætre, Simon Mork;
Rasheed, Adil.
(2023)
Digital Twin for Autonomous Surface Vessels to Generate Situational Awareness.
The American Society of Mechanical Engineers (ASME)
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
Tidsskriftspublikasjoner
-
Menges, Daniel;
Von Brandis, Andreas;
Rasheed, Adil.
(2024)
Digital Twin of Autonomous Surface Vessels for Safe Maritime Navigation Enabled through Predictive Modeling and Reinforcement Learning.
arXiv.org
Vitenskapelig artikkel
-
Menges, Daniel;
Rasheed, Adil.
(2024)
Computationally and Memory-Efficient Robust Predictive Analytics Using Big Data.
arXiv.org
Vitenskapelig artikkel
-
Menges, Daniel;
Tengesdal, Trym;
Rasheed, Adil.
(2024)
Nonlinear Model Predictive Control for Enhanced Navigation of Autonomous Surface Vessels.
arXiv.org
Vitenskapelig artikkel
-
Vaaler, Aksel;
Husa, Svein Jostein;
Menges, Daniel;
Larsen, Thomas Nakken;
Rasheed, Adil.
(2024)
Modular Control Architecture for Safe Marine Navigation: Reinforcement Learning and Predictive Safety Filters.
arXiv.org
Vitenskapelig artikkel
-
Menges, Daniel;
Rasheed, Adil.
(2023)
An environmental disturbance observer framework for autonomous surface vessels.
Ocean Engineering
Vitenskapelig artikkel
Del av bok/rapport
-
Menges, Daniel;
Sætre, Simon Mork;
Rasheed, Adil.
(2023)
Digital Twin for Autonomous Surface Vessels to Generate Situational Awareness.
The American Society of Mechanical Engineers (ASME)
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
Formidling
2023
-
Vitenskapelig foredragMenges, Daniel; Rasheed, Adil. (2023) Digital Twin for Autonomous Surface Vessels to Generate Situational Awareness. ASME OMAE 2023 42nd International Conference on Ocean, Offshore & Arctic Engineering , Melbourne, Australia 2023-06-11 - 2023-06-16
-
Faglig foredragMenges, Daniel; Håland, Joar; Brekke, Edmund Førland. (2023) SFI Autoship Webinar on Condition Monitoring. SFI Autoship webinar 2023-10-06 - 2023-10-06