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Ivan R. Bertaska

Researcher at Florida Atlantic University

Publications -  22
Citations -  517

Ivan R. Bertaska is an academic researcher from Florida Atlantic University. The author has contributed to research in topics: Control theory & Control system. The author has an hindex of 11, co-authored 22 publications receiving 394 citations. Previous affiliations of Ivan R. Bertaska include Marshall Space Flight Center.

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Journal ArticleDOI

Station-keeping control of an unmanned surface vehicle exposed to current and wind disturbances

TL;DR: An analysis of the length scales present in the power spectrum of the turbulent speed fluctuations in the wind suggests that a single anemometer is sufficient to characterize the speed and direction of the wind acting on the USV.
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Control of an Unmanned Surface Vehicle With Uncertain Displacement and Drag

TL;DR: In this paper, the performance of two low-level controllers when displacement and drag properties are time varying and uncertain is evaluated for an unmanned surface vehicle (USV) using open-loop maneuvering tests.
Proceedings ArticleDOI

Dynamics-aware target following for an autonomous surface vehicle operating under COLREGs in civilian traffic

TL;DR: A model-predictive trajectory planning algorithm for following a target boat by an autonomous unmanned surface vehicle (USV) in an environment with static obstacle regions and civilian boats and capable of making a balanced trade-off among the following, possibly conflicting criteria.
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Resolution-adaptive risk-aware trajectory planning for surface vehicles operating in congested civilian traffic

TL;DR: The results demonstrate that the basic version of the risk and contingency-aware planner (RCAP) significantly decreases the number of collisions compared to a baseline, velocity obstacles based planner, especially in complex scenarios with a high number of civilian vessels.
Journal ArticleDOI

Experimental evaluation of automatically-generated behaviors for USV operations

TL;DR: In this paper, a model-referenced trajectory planner was implemented on unmanned surface vehicles (USVs) of different size, thrust, and maneuverability characteristics, which combines a local search based on the Velocity Obstacles (VO) concept with a global, lattice-based search for a dynamically feasible trajectory.