Browsing NTNU Open by Author "Li, Guoyuan"
Now showing items 61-80 of 102
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Leveraging Past Experience for Path planning of Marine Vessel: A Docking Example
Han, Peihua; Li, Guoyuan; Zhang, Houxiang (Peer reviewed; Journal article, 2022)Path planning before maneuvering is crucial for the safe and efficient operations of marine vessels. The past successful human maneuvering experience can be leveraged to enable the safe and efficient path planning of ... -
Locomotion control of a biomimetic robotic fish based on closed loop sensory feedback CPG model
Korkmaz, Deniz; Koca, Gonca Ozmen; Li, Guoyuan; Bal, Cafer; Ay, Mustafa; Akpolat, Zuhtu Hakan (Journal article; Peer reviewed, 2019)This paper presents mechatronic design and hierarchical locomotion control of a biomimetic robotic fish for three-dimensional swimming modes. Inspired by biological features of Lamprey, a closed loop sensory feedback Central ... -
Modeling and Analysis of Motion Data from Dynamically Positioned Vessels for Sea State Estimation
Cheng, Xu; Li, Guoyuan; Skulstad, Robert; Chen, Shengyong; Hildre, Hans Petter; Zhang, Houxiang (Chapter, 2019)Developing a reliable model to identify the sea state is significant for the autonomous ship. This paper introduces a novel deep neural network model (SeaStateNet) to estimate the sea state based on the ship motion data ... -
MPC-based path planning for ship collision avoidance under COLREGS
Zhu, Mingda; Skulstad, Robert; Zhao, Luman; Zhang, Houxiang; Li, Guoyuan (Chapter, 2022)In recent years, maritime operations have become more technologically demanding due to the more complex working condition and stricter safety requirements. The need to improve the performance of human-machine cooperation ... -
Multi-sensor Data Collection and Analysis for Human Fatigue Monitoring.
Sant' Ana, Mateus (Master thesis, 2018)The human fatigue is a complex and has no universal standard to quantify or to record it. Several studies have attempted to measure with the use of machine learning techniques like Bayes Network or Deep Neural Networks. ... -
Multi-ship collision avoidance control strategy in close-quarters situations: a case study of Dover Strait ferry maneuvering
Zhao, Luman; Li, Guoyuan; Zhang, Houxiang (Chapter, 2020)Multi-ship collision avoidance is challenging in busy waters like the Dover Strait. Usually, ships follow the rules for avoiding collisions which are given by the Convention on the International Regulations for Preventing ... -
Multi-step Ship Roll Motion Prediction Based on Bi-LSTM and Input Optimization
Li, Shiyang; Wang, Tongtong; Li, Guoyuan; Skulstad, Robert; Zhang, Houxiang (Chapter, 2023)Ship roll is a crucial metric in assessing the vessel's safety in offshore operations. This paper investigates input selection for predicting short-term ship roll motion using the Bidirectional Long Short-Term Memory Network ... -
A Multilevel Convolutional Recurrent Neural Network for Blade Icing Detection of Wind Turbine
Tian, Weiwei; Cheng, Xu; Li, Guoyuan; Shi, Fan; Chen, Shengyong; Zhang, Houxiang (Peer reviewed; Journal article, 2021)Blade icing detection becomes increasingly significant as it can avoid revenue loss and power degradation. Conventional methods are usually limited by additional costs, and model-driven methods heavily depend on prior ... -
A multiple-output hybrid ship trajectory predictor with consideration for future command assumption
Kanazawa, Motoyasu; Skulstad, Robert; Li, Guoyuan; Hatledal, Lars Ivar; Zhang, Houxiang (Peer reviewed; Journal article, 2021)Onboard sensors contribute to data-driven understanding of complex and nonlinear ship dynamics in real time. By using sensors, precise ship trajectory prediction plays a key role in intelligent collision avoidance. A hybrid ... -
Navigating patterns analysis for on-board guidance support in crossing collision avoidance operations
Wu, Baiheng; Li, Guoyuan; Zhao, Luman; Aandahl, Hans-Ingar Johansen; Hildre, Hans Petter; Zhang, Houxiang (Peer reviewed; Journal article, 2021) -
Neural-network-based modelling and analysis for time series prediction of ship motion
Li, Guoyuan; Kawan, Bikram; Wang, Hao; Zhang, Houxiang (Journal article, 2017)This paper presents a data-driven model for time series prediction of ship motion. Prediction based on past time series of data is a powerful function in modern ship support systems. For a large amount of ship sensor data, ... -
A Novel Channel and Temporal-wise Attention in Convolutional Networks for Multivariate Time Series Classification
Cheng, Xu; Han, Peihua; Li, Guoyuan; Chen, Shengyong; Zhang, Houxiang (Peer reviewed; Journal article, 2020)Multivariate time series classification (MTSC) is a fundamental and essential research problem in the domain of time series data mining. Recently deep neural networks emerged as an end-to-end solution for MTSC and achieve ... -
A Novel Densely Connected Convolutional Neural Network for Sea State Estimation Using Ship Motion Data
Cheng, Xu; Li, Guoyuan; Ellefsen, Andre; Chen, Shengyong; Hildre, Hans Petter; Zhang, Houxiang (Peer reviewed; Journal article, 2020)Sea state estimation is a fundamental problem in the development of autonomous ships. Traditional methods such as wave buoy, satellites, and wave radars are limited by locations, clouds and costs, respectively. Model-based ... -
Parameter Identification of Ship Manoeuvring Model Under Disturbance Using Support Vector Machine Method
Wang, Tongtong; Li, Guoyuan; Wu, Baiheng; Æsøy, Vilmar; Zhang, Houxiang (Peer reviewed; Journal article, 2021).Demanding marine operations increase the complexity of manoeuvring. A highly accurate ship model promotes predicting ship motions and advancing control safety. It is crucial to identify the unknown hydrodynamic coefficients ... -
Path Planning of UnmannedUnderwater Vehicle (UUV ) forShortrange Fishnet Inspection Usingthe Hybrid A* Algorithm
Malisz, Michal Edward (Master thesis, 2021)This thesis present a small protion of the large motion planning domain. It focuses on the use of the Hybrid A* algorithm to generate a transverable path form A to B for underwater vehicles. The benefits is that the algorithm ... -
Physics-data Cooperative Modeling for Ship Motion Prediction
Wang, Tongtong (Doctoral theses at NTNU;2022:206, Doctoral thesis, 2022)Increasing development on autonomous vehicles and concern on ship navigation safety put forward a higher requirement for ship motion forecasting technology. The predictions of ship motion in the near future can give the ... -
Physics-data cooperative ship motion prediction with onboard wave radar for safe operations
Kanazawa, Motoyasu; Wang, Tongtong; Skulstad, Robert; Li, Guoyuan; Zhang, Houxiang (Chapter, 2023)The advancement of sensing technologies brings digitalization into the field of offshore operations. Especially, practitioners have paid attention to ensuring operational safety by predicting ship motion with motion sensors ... -
Real-time digital twin of research vessel for remote monitoring
Major, Pierre Yann; Li, Guoyuan; Zhang, Houxiang; Hildre, Hans Petter (Chapter, 2021)Real-time digital twins of ships in operation find many applications such as predictive maintenance, climbing the ladders of ship autonomy, and offshore operational excellence. The literature describes a focus on digital ... -
Real-time prediction of fish cage behaviors under varying currents using deep neural network
Gao, Sihan; Han, Peihua; Gansel, Lars Christian; Li, Guoyuan; Zhang, Houxiang (Chapter, 2023)This paper presents a Deep Neural Network (DNN) model for rapid and low-cost prediction of fish cage behavior under varying currents. We employ a numerical model of the fish cage created in Orcaflex and a set of current ... -
SAFENESS: A Semi-Supervised Transfer Learning Approach for Sea State Estimation Using Ship Motion Data
Cheng, Xu; Li, Guoyuan; Skulstad, Robert; Zhang, Houxiang (Journal article; Peer reviewed, 2023)Autonomous vessels have been identified as a promising innovation in advancing marine transportation, providing an effective means to mitigate the risk of accidents, pollution incidents, and carbon dioxide emissions. ...