Current Research Information SysTem In Norway
 
 

 English version


 
Hovedside
Forskningsresultater/NVI
Forskere
Prosjekter
Forskningsenheter
Logg inn
Om Cristin
 
 
   
Eksporter til


Viser treff 1-14 av 14

2020
1 Cheng, Xu; Li, Guoyuan; Skulstad, Robert; Chen, Shengyong; Hildre, Hans Petter; Zhang, Houxiang.
A Neural Network-Based Sensitivity Analysis Approach for Data-Driven Modeling of Ship Motion. IEEE Journal of Oceanic Engineering 2020 ;Volum 45.(2) s. 451-461
NTNU Untitled
 
2 Han, Peihua; Li, Guoyuan; Skulstad, Robert; Skjong, Stian; Zhang, Houxiang.
A Deep Learning Approach to Detect and Isolate Thruster Failures for Dynamically Positioned Vessels Using Motion Data. IEEE Transactions on Instrumentation and Measurement 2020 s. -
OCEAN NTNU Untitled
 
3 Skulstad, Robert; Li, Guoyuan; Fossen, Thor I.; Vik, Bjørnar; Zhang, Houxiang.
A Hybrid Approach to Motion Prediction for Ship Docking— Integration of a Neural Network Model into the Ship Dynamic Model. IEEE Transactions on Instrumentation and Measurement 2020 s. -
NTNU Untitled
 
2019
4 Cheng, Xu; Li, Guoyuan; Skulstad, Robert; Chen, Shengyong; Hildre, Hans Petter; Zhang, Houxiang.
Modeling and Analysis of Motion Data from Dynamically Positioned Vessels for Sea State Estimation. I: 2019 International Conference on Robotics and Automation (ICRA 2019). IEEE 2019 ISBN 978-1-5386-6027-0. s. 6644-6650
NTNU Untitled
 
5 Cheng, Xu; Li, Guoyuan; Skulstad, Robert; Major, Pierre Yann; Chen, Shengyong; Hildre, Hans Petter; Zhang, Houxiang.
Data-driven uncertainty and sensitivity analysis for ship motion modeling in offshore operations. Ocean Engineering 2019 ;Volum 179. s. 261-272
NTNU Untitled
 
6 Major, Pierre Yann; Skulstad, Robert; Li, Guoyuan; Zhang, Houxiang.
Virtual prototyping: a case study of positioning systems for drilling operations in the Barents Sea. Ships and Offshore Structures 2019 ;Volum 14.(S1) s. 364-373
NTNU Untitled
 
7 Shuai, Yonghui; Li, Guoyuan; Cheng, Xu; Skulstad, Robert; Xu, jinshan; Liu, Honghai; Zhang, Houxiang.
An efficient neural-network based approach to automatic ship docking. Ocean Engineering 2019 ;Volum 191. s. 1-9
NTNU Untitled
 
8 Skulstad, Robert; Li, Guoyuan; Fossen, Thor I.; Vik, Bjørnar; Zhang, Houxiang.
Dead reckoning of dynamically positioned ships: Using an efficient recurrent neural network. IEEE robotics & automation magazine 2019 ;Volum 26.(3) s. 39-51
NTNU Untitled
 
2018
9 Cheng, Xu; Skulstad, Robert; Li, Guoyuan; Chen, Shengyong; Hildre, Hans Petter; Zhang, Houxiang.
A data-driven sensitivity analysis approach for dynamically positioned vessels. I: Proceedings of The 59th Conference on Simulation and Modelling (SIMS 59). Linköping University Electronic Press 2018 ISBN 978-91-7685-494-5. s. 156-161
NTNU Untitled
 
10 Skulstad, Robert; Li, Guoyuan; Zhang, Houxiang; Fossen, Thor I..
A Neural Network Approach to Control Allocation of Ships for Dynamic Positioning. IFAC-PapersOnLine 2018 ;Volum 51.(29) s. 128-133
NTNU Untitled
 
2017
11 Kyllingstad, Lars Tandle; Skulstad, Robert.
MOVE project 3: Simulation technology and virtual prototyping as a common approach from design to operation. MOVE spring conference 2017; 2017-04-05
OCEAN NTNU Untitled
 
12 Skulstad, Robert.
Ship motion prediction using neural networks. Move autumn conference 2017; 2017-11-22 - 2017-11-22
NTNU Untitled
 
2015
13 Skulstad, Robert; Syversen, Christoffer Lie; Merz, Mariann; Sokolova, Nadezda; Fossen, Thor I.; Johansen, Tor Arne.
Autonomous net recovery of fixed-wing UAV with single-frequency carrier-phase differential GNSS. IEEE Aerospace and Electronic Systems Magazine 2015 ;Volum 30.(5) s. 18-27
NTNU Untitled
 
14 Skulstad, Robert; Syversen, Christoffer Lie; Merz, Mariann; Sokolova, Nadezda; Fossen, Thor I.; Johansen, Tor Arne.
Net Recovery of UAV with Single-Frequency RTK GPS. IEEE Aerospace Conference. Proceedings 2015 ;Volum 2015-June. s. -
NTNU Untitled