Blar i NTNU Open på forfatter "Skulstad, Robert"
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A data-driven sensitivity analysis approach for dynamically positioned vessels
Cheng, Xu; Skulstad, Robert; Li, Guoyuan; Chen, Shengyong; Hildre, Hans Petter; Zhang, Houxiang (Chapter, 2018) -
A Neural Network Approach to Control Allocation of Ships for Dynamic Positioning
Skulstad, Robert; Li, Guoyuan; Zhang, Houxiang; Fossen, Thor I. (Journal article; Peer reviewed, 2018)Dynamic Positioning (DP) of ships is a control mode that seeks to maintain a specific position (stationkeeping) or perform low-speed maneuvers. In this paper, a static Neural Network (NN) is proposed for control allocation ... -
A Neural Network-Based Sensitivity Analysis Approach for Data-Driven Modeling of Ship Motion
Cheng, Xu; Li, Guoyuan; Skulstad, Robert; Chen, Shengyong; Hildre, Hans Petter; Zhang, Houxiang (Journal article; Peer reviewed, 2018)Researchers have been investigating data-driven modeling as a key way to achieve ship intelligence for years. This paper presents a novel data analysis approach to data-driven modeling of ship motion. We propose a global ... -
Adaptive Data-driven Predictor of Ship Maneuvering Motion Under Varying Ocean Environments
Wang, Tongtong; Skulstad, Robert; Kanazawa, Motoyasu; Hatledal, Lars Ivar; Li, Guoyuan; Zhang, Houxiang (Chapter, 2022)Modern marine vessels operate increasingly autonomously, enabled by the strong interaction between data acquisition and analysis. The data-driven technology has been widely applied and significantly benefits maritime ... -
An efficient neural-network based approach to automatic ship docking
Shuai, Yonghui; Li, Guoyuan; Cheng, Xu; Skulstad, Robert; Xu, jinshan; Liu, Honghai; Zhang, Houxiang (Journal article; Peer reviewed, 2019)Automatic ship docking is one of the applications of autonomous ships. How to realize autonomous low-speed maneuver under environmental disturbances for docking is the fundamental problem at present. This paper presents ... -
Assessment of an Agile Concurrent Hybrid product development method for an Autonomous Mobile Forklift Concept
Perera, Pethigama Kuruvitage Hemaka Malshan (Master thesis, 2021)Agile product development has been a model of choice for product development in a changing market such as in robotics. This study focuses on determining the most appropriate product development model for robotic product ... -
A Co-operative Hybrid Model For Ship Motion Prediction
Skulstad, Robert; Li, Guoyuan; Fossen, Thor I.; Wang, Tongtong; Zhang, Houxiang (Peer reviewed; Journal article, 2021)Dynamic models of ships have been widely used for model-based control and short-term prediction in the past. Identifying the parameters of such models has mainly been done through scaled model tests, full scale tests or ... -
Co-simulation as a Fundamental Technology for Twin Ships
Hatledal, Lars Ivar; Skulstad, Robert; Li, Guoyuan; Styve, Arne; Zhang, Houxiang (Peer reviewed; Journal article, 2020)The concept of digital twins, characterized by the high fidelity with which they mimic their physical counterpart, provide potential benefits for the next generation of advanced ships. It allows analysis of data and ... -
Data-Based Modelling of Ships for Motion Prediction and Control Allocation
Skulstad, Robert (Doctoral theses at NTNU;2021:383, Doctoral thesis, 2021)Vessels operating on the surface of the ocean are exposed to an array of disturbances. These may come in terms of environmental disturbances, but may also come from signal loss. Modelling the behaviour of ships using ... -
Data-driven Uncertainty and Sensitivity Analysis for Ship Motion Modeling in Offshore Operations
Cheng, Xu; Li, Guoyuan; Skulstad, Robert; Major, Pierre Yann; Chen, Shengyong; Hildre, Hans Petter; Zhang, Houxiang (Journal article; Peer reviewed, 2019)To build a compact data-driven ship motion model for offshore operations that require high control safety, it is necessary to select the most influential parameters and to analyze the uncertainty of the input parameters. ... -
Dead Reckoning of Dynamically Positioned Ships: Using an Efficient Recurrent Neural Network
Skulstad, Robert; Li, Guoyuan; Fossen, Thor I.; Vik, Bjørnar; Zhang, Houxiang (Journal article; Peer reviewed, 2019)When a ship experiences a loss of position reference systems, its navigation system typically enters a mode known as dead reckoning (DR) to maintain an estimate of its position. Commercial systems perform this task using ... -
A Deep Learning Approach to Detect and Isolate Thruster Failures for Dynamically Positioned Vessels Using Motion Data
Han, Peihua; Li, Guoyuan; Skulstad, Robert; Skjong, Stian; Zhang, Houxiang (Peer reviewed; Journal article, 2020)Vessels today are being fully monitored, thanks to the advance of sensor technology. The availability of data brings ship intelligence into great attention. As part of ship intelligence, the desire of using advanced ... -
Design of Constraints for a Neural Network based Thrust Allocator for Dynamic Ship Positioning
Raghunathan, Rahul Nath; Skulstad, Robert; Li, Guoyuan; Zhang, Houxiang (Chapter, 2023) -
Development of a Deep Learning based Thrust Allocator for Dynamic Positioning of Fully Actuated Vessels
Raghunathan, Rahul Nath (Master thesis, 2021)Dynamic Position (DP) System is an important development in the history of marine vessels and has contributed to the development of various fields such as offshore oil and gas, offshore renewable energy, subsea pipelaying, ... -
A Digital Twin of the Research Vessel Gunnerus for Lifecycle Services: Outlining Key Technologies
Zhang, Houxiang; Li, Guoyuan; Hatledal, Lars Ivar; Chu, Yingguang; Ellefsen, André Listou; Han, Peihua; Major, Pierre Yann; Skulstad, Robert; Wang, Tongtong; Hildre, Hans Petter (Journal article; Peer reviewed, 2022) -
An effective model-based thruster failure detection method for dynamically positioned ships
Wang, Tongtong; Li, Guoyuan; Skulstad, Robert; Æsøy, Vilmar; Zhang, Houxiang (Chapter, 2020)This paper presents an effective model-based thruster failure detection and isolation method for dynamically positioned (DP) offshore surface vessels. A DP vessel is supposed to maintain its position and heading at a ... -
A Hybrid Approach to Motion Prediction for Ship Docking— Integration of a Neural Network Model into the Ship Dynamic Model
Skulstad, Robert; Li, Guoyuan; Fossen, Thor I.; Vik, Bjørnar; Zhang, Houxiang (Peer reviewed; Journal article, 2020)While automatic controllers are frequently used during transit operations and low-speed maneuvering of ships, ship operators typically perform docking maneuvers. This task is more or less challenging depending on factors ... -
Incorporating Approximate Dynamics Into Data-Driven Calibrator: A Representative Model for Ship Maneuvering Prediction
Wang, Tongtong; Li, Guoyuan; Hatledal, Lars Ivar; Skulstad, Robert; Æsøy, Vilmar; Zhang, Houxiang (Peer reviewed; Journal article, 2021)High-fidelity models capable of accurately predicting ship motion are critical for promoting innovation and efficiency in the maritime industry. However, creating an advanced model that comprehensively represents the system ... -
Knowledge and data in cooperative modeling: Case studies on ship trajectory prediction
Kanazawa, Motoyasu; Wang, Tongtong; Skulstad, Robert; Li, Guoyuan; Zhang, Houxiang (Peer reviewed; Journal article, 2022)A ship automation will be a key to the future maritime. In particular, ship dynamic models play an integral role. However, it is challenging to develop an accurate model readily. Recent studies proposed a physics-data ... -
Knowledge transfer strategy for enhancement of ship maneuvering model
Wang, Tongtong; Skulstad, Robert; Kanazawa, Motoyasu; Li, Guoyuan; Zhang, Houxiang (Peer reviewed; Journal article, 2023)The advancement of autonomous vehicles and concerns about ship navigation safety have resulted in a greater need for ship model quality. However, in situations where there is limited prior information or data available ...