Journal ArticleDOI
AUV Navigation and Localization: A Review
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TLDR
A review of the state of the art of AUV navigation and localization, as well as a description of some of the more commonly used methods, are presented and areas of future research potential are highlighted.Citations
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Journal ArticleDOI
Digital Twin: Values, Challenges and Enablers From a Modeling Perspective
TL;DR: This work reviews the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.
Journal ArticleDOI
Multiple-Robot Simultaneous Localization and Mapping: A Review
TL;DR: Various issues and problems in multiple-robot SLAM are introduced, current solutions for these problems are reviewed, and their advantages and disadvantages are discussed.
Journal ArticleDOI
Advancements in the field of autonomous underwater vehicle
TL;DR: Current research trends in the field of AUVs and future research directions are presented and localization and navigation techniques such as inertial navigation to simultaneous localization and mapping being used in current AUVs are discussed in detail.
Journal ArticleDOI
Integral Line-of-Sight Guidance and Control of Underactuated Marine Vehicles: Theory, Simulations, and Experiments
Walter Caharija,Kristin Y. Pettersen,Marco Bibuli,Pedro Calado,Enrica Zereik,José Braga,Jan Tommy Gravdahl,Asgeir J. Sørensen,Milan Milovanovic,Gabriele Bruzzone +9 more
TL;DR: An extensive analysis of the integral line-of-sight (ILOS) guidance method for path-following tasks of underactuated marine vehicles, operating on and below the sea surface shows that due to the embedded integral action, the guidance law makes the vessels follow straight lines by compensating for the drift effect of environmental disturbances.
Journal ArticleDOI
Formation Learning Control of Multiple Autonomous Underwater Vehicles With Heterogeneous Nonlinear Uncertain Dynamics
TL;DR: A new concept of formation learning control is introduced to the field of formation control of multiple autonomous underwater vehicles (AUVs), which specifies a joint objective of distributed formation tracking control and learning/identification of nonlinear uncertain AUV dynamics.
References
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Object recognition from local scale-invariant features
TL;DR: Experimental results show that robust object recognition can be achieved in cluttered partially occluded images with a computation time of under 2 seconds.
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Speeded-Up Robust Features (SURF)
TL;DR: A novel scale- and rotation-invariant detector and descriptor, coined SURF (Speeded-Up Robust Features), which approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster.
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Gaussian Processes for Machine Learning
TL;DR: The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics, and deals with the supervised learning problem for both regression and classification.
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Probabilistic Robotics
TL;DR: This research presents a novel approach to planning and navigation algorithms that exploit statistics gleaned from uncertain, imperfect real-world environments to guide robots toward their goals and around obstacles.
Journal ArticleDOI
The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model
TL;DR: In this paper, a split-explicit hydrodynamic kernel for a realistic oceanic model is proposed, which addresses multiple numerical issues associated with mode splitting, and is compatible with a variety of centered and upstream-biased high-order advection algorithms, and helps to mitigate computational cost of expensive physical parameterization of mixing processes and submodels.