CurviTrack: Curvilinear Trajectory Tracking for High-Speed Chase of a USV

Heterogeneous robot teams used in marine environments incur time-and-energy penalties when the marine vehicle has to halt the mission to allow the autonomous aerial vehicle to land for recharging. In this paper, we present a solution for this problem using a novel drag-aware model formulation which is coupled with Model Predictive Control (MPC), and therefore, enables tracking and landing during high-speed curvilinear trajectories of an Uncrewed Surface Vehicle (USV) without any communication. Compared to the state-of-the-art, our approach yields 40% decrease in prediction errors, and provides a 3-fold increase in certainty of predictions. Consequently, this leads to a 30% improvement in tracking performance and 40% higher success in landing on a moving USV even during aggressive turns that are unfeasible for conventional marine missions. We test our approach in two different real-world scenarios with marine vessels of two different sizes and further solidify our results through statistical analysis in simulation to demonstrate the robustness of our method.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2025-02-26
DOI
https://doi.org/10.1109/lra.2025.3546079
Citations
3
Primary Topic
Vehicle Dynamics and Control Systems
Type
article
Field-Weighted Citation Impact
2.05
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article

CurviTrack: Curvilinear Trajectory Tracking for High-Speed Chase of a USV

Martin Saska, Parakh M. Gupta, Tiago Nascimento, Ondřej Procházka
3 citations
IEEE Robotics and Automation Letters
Vehicle Dynamics and Control Systems
2.05
article

CurviTrack: Curvilinear Trajectory Tracking for High-Speed Chase of a USV

Martin Saska, Parakh M. Gupta, Tiago Nascimento, Ondřej Procházka
article en
3 citations

Abstract

Heterogeneous robot teams used in marine environments incur time-and-energy penalties when the marine vehicle has to halt the mission to allow the autonomous aerial vehicle to land for recharging. In this paper, we present a solution for this problem using a novel drag-aware model formulation which is coupled with Model Predictive Control (MPC), and therefore, enables tracking and landing during high-speed curvilinear trajectories of an Uncrewed Surface Vehicle (USV) without any communication. Compared to the state-of-the-art, our approach yields 40% decrease in prediction errors, and provides a 3-fold increase in certainty of predictions. Consequently, this leads to a 30% improvement in tracking performance and 40% higher success in landing on a moving USV even during aggressive turns that are unfeasible for conventional marine missions. We test our approach in two different real-world scenarios with marine vessels of two different sizes and further solidify our results through statistical analysis in simulation to demonstrate the robustness of our method.

IEEE Robotics and Automation LettersVol. 10(4)
Czech Technical University in Prague (CZ)
Openalex Percentile: Top 15%
Vehicle Dynamics and Control Systems
2.05
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