Trajectory Tracking with Collision Avoidance for Large Vessel Draft Surveys
Permanent lenke
https://hdl.handle.net/10037/34162Dato
2024-05-15Type
Master thesisMastergradsoppgave
Forfatter
Saleheen, A B MSammendrag
This thesis explores the innovative use of unmanned aerial vehicles to conduct draft surveys of large maritime vessels. This process is critical for
determining vessel load through water displacement measurements. At the
port of Narvik, a crew typically performs this task manually, where LKAB’s
iron ore cargo vessels are surveyed while docked. The usual method requires
going around the ship in a small boat to check draft markings, which can be
difficult, especially in bad weather or at dark times. The close quarters and
dangerous conditions often create safety risks and operational difficulties.
The primary aim of this research is to automate the draft survey pro-
cess by using a self-flying quadrotor that is equipped with an autonomous
guidance and control system. This system utilizes Nonlinear Model Predictive Control for precise position control, allowing for optimal trajectory
tracking and effective collision avoidance, along with a reduced attitude controller. The goal is for the UAV to autonomously follow a predetermined
path around the vessel, and systematically capture images or videos of the
draft markings for analysis.
This research presents a theoretical model and simulation framework for
implementing the developed system. The findings contribute to the field
of UAV applications in the maritime sector by proposing an integration
of control theory, UAV technology, and maritime operation needs. This
study not only paves the way for further technological advancements in
autonomous UAV systems but also enhances our understanding of their
practical implementations in industry-specific scenarios.
Forlag
UiT Norges arktiske universitetUiT The Arctic University of Norway
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