L
Lars Ivar Hatledal
Researcher at Norwegian University of Science and Technology
Publications - 28
Citations - 302
Lars Ivar Hatledal is an academic researcher from Norwegian University of Science and Technology. The author has contributed to research in topics: Virtual prototyping & Computer science. The author has an hindex of 10, co-authored 24 publications receiving 207 citations. Previous affiliations of Lars Ivar Hatledal include Aalesund University College.
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Journal ArticleDOI
Controlling Kuka Industrial Robots: Flexible Communication Interface JOpenShowVar
TL;DR: Even though only soft real-time applications can be implemented, JOpenShowVar opens up to a variety of possible applications, making the use of various input devices and sensors as well as the development of alternative control methods possible.
Proceedings ArticleDOI
JOpenShowVar: An open-source cross-platform communication interface to Kuka robots
TL;DR: JOpenShowVar, a Java open-source cross-platform communication interface to Kuka robots that allows for reading and writing variables and data structures of the controlled manipulators, is introduced.
Journal ArticleDOI
Integrated Flexible Maritime Crane Architecture for the Offshore Simulation Centre AS (OSC): A Flexible Framework for Alternative Maritime Crane Control Algorithms
TL;DR: This integration establishes the base for the research of alternative control algorithms, which can be efficiently tested in a realistic maritime simulation environment, and an alternative control method based on particle swarm optimization (PSO) is presented.
Journal ArticleDOI
Virtual prototyping for maritime crane design and operations
TL;DR: The proposed virtual prototyping system for maritime crane design and operations introduces an open and flexible platform, and the virtual simulator for operations based on the proposed framework is reinforced by high fidelity models of physics and dynamics.
Journal ArticleDOI
Incorporating Approximate Dynamics Into Data-Driven Calibrator: A Representative Model for Ship Maneuvering Prediction
TL;DR: A hybrid modeling methodology is proposed, in which prior knowledge describing the ship dynamic effects is incorporated into a data-driven calibrator, yielding a representative model with high predictive capability and shows that the cooperative model greatly improves the predictive capability of the research vessel.