Guoyuan Li
Guoyuan Li
Associate Professor, NTNU
Verified email at - Homepage
Cited by
Cited by
Big data and industrial internet of things for the maritime industry in northwestern norway
H Wang, OL Osen, G Li, W Li, HN Dai, W Zeng
TENCON 2015-2015 IEEE Region 10 Conference, 1-5, 2015
Development of adaptive locomotion of a caterpillar-like robot based on a sensory feedback CPG model
G Li, H Zhang, J Zhang, RT Bye
Advanced Robotics 28 (6), 389-401, 2014
Analysis and design of asymmetric oscillation for caterpillar-like locomotion
G Li, W Li, J Zhang, H Zhang
Journal of Bionic Engineering 12 (2), 190-203, 2015
Analysis and modeling of sensor data for ship motion prediction
G Li, B Kawan, H Wang, A Styve, OL Osen, H Zhang
MTS/IEEE Oceans Conference 2016, 2016
A novel mechanism for caterpillar-like locomotion using asymmetric oscillation
G Li, H Zhang, F Herrero-Carrón, F Herrero-Carrón, HP Hildre, J Zhang
2011 IEEE/ASME International Conference on Advanced Intelligent Mechatronics …, 2011
A Bio-inspired Swimming Robot for Marine Aquaculture Applications: from Concept-design to Simulation
G Li, Y Deng, OL Osen, S Bi, H Zhang
MTS/IEEE Oceans Conference 2016, 2016
Online learning control of surface vessels for fine trajectory tracking
G Li, W Li, HP Hildre, H Zhang
Journal of Marine Science and Technology 21 (2), 251-260, 2016
Neural-network-based modelling and analysis for time series prediction of ship motion
G Li, B Kawan, H Wang, H Zhang
Ship technology research 64 (1), 30-39, 2017
Towards data-driven identification and analysis of propeller ventilation
H Wang, S Fossen, F Han, IA Hameed, G Li
OCEANS 2016-Shanghai, 1-6, 2016
Data integration and visualisation for demanding marine operations
H Wang, X Zhuge, G Strazdins, Z Wei, G Li, H Zhang
OCEANS 2016-Shanghai, 1-7, 2016
An approach for adaptive limbless locomotion using a CPG-based reflex mechanism
G Li, H Zhang, J Zhang, HP Hildre
Journal of Bionic Engineering 11 (3), 389-399, 2014
Hierarchical control of limbless locomotion using a bio-inspired cpg model
G Li
Flexible Modular Robotic Simulation Environment For Research And Education.
D Krupke, G Li, J Zhang, H Zhang, HP Hildre
ECMS, 243-249, 2012
Simplifying neural network based model for ship motion prediction: a comparative study of sensitivity analysis
X Cheng, S Chen, C Diao, M Liu, G Li, H Zhang
International Conference on Offshore Mechanics and Arctic Engineering 57632 …, 2017
An efficient neural-network based approach to automatic ship docking
Y Shuai, G Li, X Cheng, R Skulstad, J Xu, H Liu, H Zhang
Ocean Engineering 191, 106514, 2019
Dead reckoning of dynamically positioned ships: Using an efficient recurrent neural network
R Skulstad, G Li, TI Fossen, B Vik, H Zhang
IEEE Robotics & Automation Magazine 26 (3), 39-51, 2019
Data-driven uncertainty and sensitivity analysis for ship motion modeling in offshore operations
X Cheng, G Li, R Skulstad, P Major, S Chen, HP Hildre, H Zhang
Ocean Engineering 179, 261-272, 2019
A neural-network-based sensitivity analysis approach for data-driven modeling of ship motion
X Cheng, G Li, R Skulstad, S Chen, HP Hildre, H Zhang
IEEE Journal of Oceanic Engineering 45 (2), 451-461, 2019
Towards A Virtual Prototyping Framework for Ship Maneuvering in Offshore Operations
G Li, PB Skogeng, Y Deng, LI Hatledal, H Zhang
MTS/IEEE Oceans Conference 2016, 2016
A Novel Densely Connected Convolutional Neural Network for Sea State Estimation Using Ship Motion Data
X Cheng, G Li, AL Ellefsen, S Chen, HP Hildre, H Zhang
IEEE Transactions on Instrumentation and Measurement, 2020
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