A domain-specific architecture framework for the maritime domain
(Benjamin Weinert)

Die internationale maritime Domäne muss sich der Herausforderung stellen, existierende heterogene Systeme zu harmonisieren sowie künftige Systeme und Technologien in ihre existierenden technischen Strukturen bzw. Organisationsstrukturen für eine nachhaltige, sichere und zuverlässige Schifffahrt zu integrieren. Dieser Vorgang betrifft technische Komponenten, Organisationsstrukturen und dem menschlichen Nutzer gleichermaßen. Entsprechend der e-Navigation vision der International Maritime Organization (IMO) für eine nahtlose Integration von existierenden und neuen Systemen, müssen diese in strukturierter und standardisierter Weise hinsichtlich technischer oder operationaler Faktoren entsprechend ihres Einsatzgebietes analysiert werden. Eine solche strukturierte Analyse ermöglicht es den maritimen Stakeholdern Beziehungen und Zusammenhänge zwischen der maritimen Welt und den betrachteten sozio-technischen Systemen zu identifizieren und bei künftigen (Weiter-)entwicklungen zu berücksichtigen. In Anlehnung an sogenannte Enterprise Architecture Frameworks, kann ein domänen-spezifisches Architecture Framework eine einheitliche Methodik bereitstellen um den Konstruktionsprozess sozio-technischer Systeme sowie die Integration in bestehende Systeme zu unterstützen. Solch ein maritimes Architecture Framework muss entsprechend die maritime Welt und ihre Strukturen berücksichtigen. Dazu gehören etwa Stakeholder, existierende und neue Technologien sowie existierende Geschäftsprozesse und Organisationsstrukturen auf nationaler, regionaler und internationaler Ebene.

Sensor Integration and Control of Marine Vehicles
(Chen Zhang)

In a marine vehicle control system, sensors data include body positions, orientation and trajectory, and the ocean environment, human reports, etc. Therefore, sensor integration is a necessary technique to synthesize all the sensors data to provide more reliable and accurate information. Nevertheless, coupling, drifting and other errors are always included in the measured sensors data, the classic method to deal with the data is kalman filter or extended kalman filter estimation, and they result in estimates for the fused sensors data that are optimal in a statistical sense. However, there could still be some unexpected errors causing wrong behavior of estimated ship’s dynamic, so as a candidate solution, fault-tolerant control can detect and prevent those unacceptable errors and limit the remaining errors within a safe range, in order to control the vehicles with the desired motion on its predefined trajectory.

Damage Mitigation Techniques of ship collisions and grounding.
(Hasan Youseff Deeb)

My research topic concerns the phase of encountering situation between two vessels, where collision is not avoidable anymore. it focuses on defining the main collision scenario variables and investigates the ability to use such collision scenario variables in order to minimize the expected damages. e.g. effects of collision angle, speed and collision location (structural distribution) on impact energy and damage volume. My research will investigate the ability to use ship maneuvering capabilities in order to modify such collision scenario variables to reduce collision impact energy i.e. Provide emergency steering guideline (Algorithm) to make evasive maneuvering more wiser once collision is inevitable. same applies for grounding accidents with known shallow water area.

Ereigniserkennung in spatiotemporalen Schiffsdaten mit Datenstrommanagementsystemen
(Tobias Brandt)

Spatio-temporal data describes data with additional information about location and time. The amount of spatio-temporal data increases rapidly, as mobile devices with satellite based navigation systems, such as GPS, are becoming smaller and widely available. Not only smartphones, but planes, ships or even animals can be equipped with location sensors. With an additional internet connection, they can send their position in near real time and can attach additional measurements, such as the temperature, destination or height.Such data, especially if it is send live via an internet connection and the amount of data is very high, is difficult to oversee by humans. Data mining on spatio-temporal data is therefore needed to find common patterns, detect anomalies or predict future developments. If the data is send live in near real time, the processing of the data should be done in near real-time as well to get fast results. In addition, the high amount of very detailed data may be too much to save everything in a database and analyze it afterwards. Therefore, data stream processing is a useful approach for such data. Here, not all data is stored permanently but the processing is done on a smaller, more relevant set of the data.This research topic aims to analyze, use and improve concepts for spatio-temporal anomaly detection on data streams. The concepts can for example be evaluated on AIS (Automatic Identification System) data from vessels, which contain the current position of the vessel as well as it's identification number and destination among others. The evaluation can be done within the Odysseus Data Stream Management System (see 

Multi-Tenancy/Multi-User Architecture for Data Stream Management Systems in Maritime Applications – Resource Management, Privacy and Isolation Aspects
(Hendrik Müller)

Description language for environment scenarios generation for maritime simulations
(Liqun Wu)

Environment scenarios in vessel simulation contains various environment factors that influence the movement of the vessels. These scenarios play crucial roles in multi-agent vessel simulations and usually are assumed to be given. However, in practice, they are not always available. Firstly, maritime experts desire to see different kinds of edge cases, such as how the ship move through the ocean under extreme weather conditions. Using the existing observation data or prediction data, it is unlikely to cover every cases. On the other hand, the experts may want to manipulate the behavior of the factors, e.g. speeding-up the wind at a stable frequency. Existing datasets does not provide this kind of freedom. It becomes time-costly when maritime experts have to switch their focus to the structure of spatial-temporal coverage data, trying to generating scenarios which satisfy their needs. This research aims at providing a formal description language together with its execution engine, to solve the above-mentioned problem. It frees the maritime experts from understanding how the spatial-temporal coverage data is organized and generated. The language grammar allows them describing the properties and behavior of the marine environment factors using the domain abstractions they are familiar with. The execution engine renders the scenario file to generate a corresponding spatial-temporal data frame, fills in the suitable values of required environment factors. By changing the description, the scenarios can be easily modified.

Ship Dynamic Modeling, and Identification Using Observation Data
(Man Zhu)

To devise and implement a control strategy giving a vessel the ability to robustly and accuratedly predict trajectories of own and others that span the vessel's entire performance envelope. To fulfill this task a model which is sufficiently rich to enable effective motion planning and control and sufficiently simple to allow straight forward parameter identification much be selected from a set of simple models whose parameters can be quickly and easily identified from standard motion data. Having selected an appropriate model, dynamically feasible trajectories can be predicted by using AIS data for the own ship and other ships to take action for avoiding collision. An effective closed-loop control algorithm then enables predicting aggressive trajectories in the presence of environmental disturbances and modelling uncertainties.

Nonlinear Model Predictive Control for Path following and Collision Avoidance
(Mohamed Abdelaal)

My research problem is representation of path following and collision avoidance of vessels as a Multi agent dynamic game with an objective to optimize a coupled payoff function subject to the dynamics of our vessel and the nearby vessels. In order for that collision avoidance system to be efficient, the algorithm must predict other ships states to avoid any future possible collision in a finite predetermined horizon. So, the dynamic game will be modified to include the predicted states in the coupled cost function and solve the optimization problem at every sample in a moving horizon manner. This is called in the literature distributed model predictive control (DMPC). To guarantee Collision avoidance, the time delay in predicting other nearby vessels must be taken into consideration and not neglected.

Integrated nautical Maneuver planning for modern SHIPcontroller
(Oliver Köckritz)

Modern steering devices for ships lead to an improved control capability and allow independent actions without tugs by mates in use with modern electronics. Within the project AdaNav developed MIMO controller enables DP equivalent functions for ships being able to traverse. The dissertation will discribe in theorie and practice the inclusion of such modern maneuvering quality as computer based assistance system into electronic ship guidance systems like ECDIS. To guarantee fully responsibility of mates the concept bases on introduced planning practice implementing additional waypoints and attributes in a so-called kinematic sequence. This kinematic sequence connects the developed integrated nautical user interface and the existing MIMO controller of the AdaNav project.

Event detection for maritime time-series data with computational intelligence
(Stefan Ohemcke)

The growing infrastructures of information and sensor systems in the marine domain lead to an increased demand of data mining solutions. Especially time series data from sensor platforms with high dimensionality create massive amounts of data daily. Possible application with such data are event or outlier detection and value prediction for forecasts. The problems of existing methods are that often data are handled if they are univariate or the time relation is ignored. Further, this real data is prone to become missing and having high noise rate, which results in a decrease in the usefulness of data. My first publication was about the marine event detection with data from the sensor platform at Spiekeroog. The applied machine learning algorithm was local outlier factors and tested three different preprocessing methods. Evaluation was conducted with help of domain experts, who classified found events as positives or false-positives. The results indicate that events of interest to domain experts can be found with an accuracy of 80% and the preprocessing is crucial for the success of event detection. The next step is repairing missing data to enable analysis of complete data. For example, I had to exclude a whole month from the event detection, because the algorithm could not process incomplete data. I utilize dynamic time warping and a simple interpolation step to address the specific problems of missing data from sensor platforms, which can be conclusively missing and multiple missing values at the same time. In future work I will use Machine Learning to perform predictions of values that are in another place of the ocean to augment sensor platforms with measurements they can’t conduct at this time, e.g. for the BEFmate project. This will feature multiple data sources at once from the Cosyna project. Also, more in depth detection of ocean events are planned.

Evaluation of Distributed Situation Awareness on a Ship Bridge 
(Stella Parisi)

Situation Awareness (SA) is an important cognitive aspect of the decision making activities on a ship bridge. The navigation crew uses the bridge systems to gather information elements and gain SA. Designers need to understand the SA requirements of the crew and develop systems with user interfaces (UI) that support these requirements. The existing methods for evaluating SA are more fitting for assessing the SA of individuals rather than the Distributed Situation Awareness (DSA) that characterises the ship bridge environment. This paper proposes a model-based approach for the evaluation of DSA that can be used in early system design stages. The methodology will use fuzzy cognitive mapping techniques to represent the DSA requirements of the crew. The anticipated results include a cause-effect analysis tool and suggestions for UI design of intelligent systems.

Improving the situation awareness of OOWs by tracking and shifting their visual spatial attention
(Tim Claudius Stratmann)

With ships becoming bigger and bigger, navigation and maneuvering without the given technology has become nearly impossible. Seafarers have to rely on information given by their navigational and assistive systems. I am aiming to improve the situation awareness of officers of the watch by optimizing their monitoring behavior. To achieve this, I will track the visual spatial attention of the officer of the watch and shift it to areas with potentially unseen critical information. This should lower the risk of sea accidents such as collisions and grounding.

Be aware of your surrounding - Visualization of dynamic
Off-Screen objects and Attention Shift in head-mounted Augmented Reality

(Uwe Wilko Grünefeld)

Moderne Arbeitsumgebungen sind für Menschen immer noch ein große
Herausforderung. Dies liegt oft an den weitläufig verteilten relevanten
Bereichen die für eine Person unmöglich gleichzeitig im Blick zu halten
sind. Ein Beispiel für eine solche Arbeitsumgebung ist die Schiffsbrücke
großer Containerschiffe. In vielen unterschiedlichen Szenarien sind auf
der Schiffsbrücke nicht nur unzählige Monitore im Blick zu halten,
sondern auch andere Schiffe, Bojen, Schlepper und Kaimauern. Verglichen
mit dem eingeschränkten Sichtfeld des Menschen und dem noch kleineren
Bereich im Sichtfeld in dem fokussiert werden kann wird deutlich, dass
unmöglich alle Objekte zur selben Zeit betrachtet werden können. In
meiner Arbeit soll eine Lösung auf Basis von head-mounted Augmented
Reality erarbeitet werden, die es erlaubt diese Objekte außerhalb des
menschlichen Fokus zu visualisieren (sogenannte Off-Screen Objekte) und
wenn nötig, die Aufmerksamkeit auf diese Objekte zu lenken. Die visuelle
Modalität soll verwendet werden, weil auditive und taktile Signale auf
Grund der hohen Informationsdichte und der Komplexität der Information
ungeeignet sind z.B. viele Off-Screen Objekte zur selben Zeit mit
Distanz- und Typinformationen die immer wieder Ihre Position ändern und
weil z.B. die auditive Modalität über Funksprüche, Alarme und
Kommunikation bereits stark ausgelastet ist. Darüber hinaus wird
head-mounted Augmented Reality verwendet, weil die normalen
Arbeitsabläufe möglichst nicht gestört werden sollen z.B. weil die Hände
frei bleiben und damit die Informationen nur einer Person gezielt
zugespielt werden.

Entwicklung eines MIMO Regelframeworks als universell nutzbares Navigationsregelungssystem
(D. Grunert)

Moderne Seefahrzeuge besitzen zur besseren Steuerbarkeit und Energieeffizienz 
moderne Antriebssysteme wie verstellbare Propellergondeln oder Strahlruder. Im 
Rahmen dieser Thesis soll untersucht werden, inwiefern sich die zur 
automatischen Regelung dieser Antriebe notwendige Parametrierung durch Bildung 
von Abstraktionsmodellen vereinfachen, generalisieren oder automatisieren 
lässt, um ein flexibel einsetzbares, zuverlässiges Regelsystem zu ermöglichen.

Weiterentwicklung von Algorithmen zur automatischen Detektion von kleinen, nicht‐ metallischen, maritimen Artefakten mit Hilfe von Radar‐Fernerkundungsdaten
(Peter Lanz)

Das Forschungsprojekt verfolgt das Ziel der Weiterentwicklung von Methoden zur automatischen Detektion kleiner, nicht metallischer Artefakte auf der Meeresoberfläche mit Hilfe von Radar‐ Satellitendaten. Am Ende soll eine rasche, automatische Verortung von Zielartefakten in diesem (theoretisch) kontinuierlich verfügbaren Datenstroms an Radardaten realisiert werden können. Die technische Umsetzung dieses Ziels könnte einen wichtigen Baustein zur Unterstützung von Search&Rescue Missionen darstellen und damit schnelle und tragfähige Krisenintervention ermöglicht. Ein anschauliches Produkt könnte auch ein öffentlich zugänglicher Webdienst sein, der die Ergebnisse in naher Echt‐Zeit interaktiv visualisiert. Eine weitere Anwendung könnte die verbesserte Ortung von maritimen Kunststoffmülls bedeuten. Vor dem Hintergrund der rasanten Entwicklung im Bereich der Satellitentechnologien und der raschen Zunahme an operablen Satellitensystemen, ist in den kommenden Jahren von einer steten Zunahme verfügbarer Satellitendaten in immer höherer zeitlicher und räumlicher Auflösung auszugehen. Diese Entwicklungen stellt eine wichtige Perspektive für die Weiterentwicklung von Auswertemethoden und Diversifizierung der daraus ableitbaren Anwendungen dar; in, und über das vorliegende Projekt hinaus.

Underwater acoustic system integration with maritime test-beds for ship maneuvering parameter extraction
(A. Aljuhne)

Extending the service provided by maritime test beds with systems that remotely extract extra information from passing vessels without the need of direct cooperation is a potential advancement. The project aims to develop a new system that uses underwater acoustic technologies, and integrate it with available maritime systems. This integration enables the extraction of new set of information that serves several applications in the maritime domain. The maneuvering parameters such as propeller speed and rudder angle change play key role in ship behavior prediction application and environmental monitoring fields.

(Stand: 19.01.2024)  | 
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