arXiv subjects

Fredrik Ljungberg

Publications and source records attributed to Fredrik Ljungberg.

3 recordsLinked to original sources

arXiv2026

Vessel Trajectory Prediction using COLREGs-aware Optimal Planning

This paper presents a trajectory prediction method for marine vessels based on optimal planning. Crude initial trajectories respecting static obstacles are first generated using A*-search to provide a feasible warm start. In the second step, a numerical optimizer is used to ensure COLREG compliance. The prediction problem is posed as sequential trajectory planning from the perspective of each surrounding vessel, requiring only their current positions, velocities, and intended destinations as input. As the latter is included in AIS messages, this enables faster predictions than learning-based methods that typically require longer data histories. The proposed method is validated using real-world scenarios constructed from AIS data.

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arXiv2022

Experiment Design for Identification of Marine Models

In this work, experiment design for marine vessels is explored. A dictionary-based approach is used, i.e., a systematic way of choosing the most informative combination of independent experiments out of a predefined set of candidates. This idea is quite general but is here tailored to an instrumental variable (IV) estimator with zero-mean instruments. This type of estimator is well-suited to deal with parameter estimation for second-order modulus models, which is a class of models often used to describe motion of marine vessels. The method is evaluated using both simulated and real data, the latter from a small model ship as well as from a full-scale vessel. Further, a standard motion-planning problem is modified to account for the prior-made choice of information-optimal sub-experiments, which makes it possible to obtain a plan for the complete experiment in the form of a feasible trajectory.

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arXiv2022

Consistent Estimators for Nonlinear Vessel Models

In this work, the issue of obtaining consistent parameter estimators for nonlinear regression models where the regressors are second-order modulus functions is explored. It is shown that consistent instrumental variable estimators can be obtained by estimating first and second-order moments of non-additive environmental disturbances' probability distributions as nuisance parameters in parallel to the sought-after model parameters, conducting experiments with a static excitation offset of sufficient amplitude and forcing the instruments to have zero mean. The proposed method is evaluated in a simulation example with a model of a marine surface vessel.

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