Robin T. Bye
Robin T. Bye
Professor and Head of Cyber-Physical Systems Lab, Department of ICT and Natural Sciences, NTNU
Verified email at ntnu.no - Homepage
Title
Cited by
Cited by
Year
The BUMP model of response planning: Variable horizon predictive control accounts for the speed–accuracy tradeoffs and velocity profiles of aimed movement
RT Bye, PD Neilson
Human movement science 27 (5), 771-798, 2008
352008
The BUMP model of response planning: intermittent predictive control accounts for 10 Hz physiological tremor
RT Bye, PD Neilson
Human movement science 29 (5), 713-736, 2010
332010
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
262014
A Receding Horizon Genetic Algorithm for Dynamic Resource Allocation: A Case Study on Optimal Positioning of Tugs
RT Bye
Studies in Computational Intelligence, 131-147, 2012
162012
A computer-automated design tool for intelligent virtual prototyping of offshore cranes
RT Bye, O Osen, BS Pedersen
29th European Conference on Modelling and Simulation,{ECMS} 2015, Albena …, 2015
152015
The teacher as a facilitator for learning: Flipped classroom in a master's course on artificial intelligence
RT Bye
9th International Conference on Computer Supported Education (CSEDU '17) 1 …, 2017
14*2017
AN IMPROVED RECEDING HORIZON GENETIC ALGORITHM FOR THE TUG FLEET OPTIMISATION PROBLEM
RT Bye, HG Schaathun
Proceedings of the 28th European Conference on Modelling and Simulation, 682 …, 2014
132014
A game-based learning framework for controlling brain-actuated wheelchairs
RM Hjørungdal, F Sanfilippo, O Osen, A Rutle, RT Bye
30th European Conference on Modelling and Simulation, Regensburg Germany …, 2016
122016
Grey wolf optimizer (GWO) for automated offshore crane design
IA Hameed, RT Bye, OL Osen
2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-6, 2016
112016
Evaluation Heuristics for Tug Fleet Optimisation Algorithms-A Computational Simulation Study of a Receding Horizon Genetic Algorithm
RT Bye, HG Schaathun
International Conference on Operations Research and Enterprise Systems 2 …, 2015
112015
Aktiv læring i mikrokontrollarar
WA Schaathun, HG Schaathun, RT Bye
Uniped 38 (04), 381-389, 2015
102015
A RECEDING HORIZON GENETIC ALGORITHM FOR DYNAMIC MULTI-TARGET ASSIGNMENT AND TRACKING-A Case Study on the Optimal Positioning of Tug Vessels along the Northern Norwegian Coast
RT Bye, SB van Albada, H Yndestad
International Conference on Evolutionary Computation 2, 114-125, 2010
102010
A software framework for intelligent computer-automated product design
RT Bye, O Osen, BS Pedersen, I Hameed, HG Schaathun
30th European Conference on Modelling and Simulation, Regensburg Germany …, 2016
92016
On usage Of EEG brain control for rehabilitation of stroke patients
T Verplaetse, F Sanfilippo, A Rutle, O Osen, RT Bye
30th European Conference on Modelling and Simulation, Regensburg Germany …, 2016
82016
Intelligent computer-automated crane design using an online crane prototyping tool
I Hameed, RT Bye, O Osen, BS Pedersen, HG Schaathun
30th European Conference on Modelling and Simulation, Regensburg Germany …, 2016
82016
A SUSTAINABLE MODEL FOR OPTIMAL DYNAMIC ALLOCATION OF PATROL TUGS TO OIL TANKERS
B Assimizele, J Oppen, RT Bye
European Conference on Modelling and Simulation, 801-807, 2013
82013
A Riemannian geometry theory of human movement: The geodesic synergy hypothesis
PD Neilson, MD Neilson, RT Bye
Human movement science 44, 42-72, 2015
72015
Preventing environmental disasters from grounding accidents: A case study of tugboat positioning along the Norwegian coast
B Assimizele, JO Royset, RT Bye, J Oppen
Journal of the Operational Research Society 69 (11), 1773-1792, 2018
62018
A Flipped Classroom Approach for Teaching a Master’s Course on Artificial Intelligence
RT Bye
International Conference on Computer Supported Education, 246-276, 2017
62017
Reflections on Teaching Electrical and Computer Engineering Courses at the Bachelor Level.
OL Osen, RT Bye
CSEDU (2), 57-68, 2017
62017
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