Delea, CosminCosminDeleaZantopp, NicoNicoZantoppEssa, MohamedMohamedEssaSchmid, MatteoMatteoSchmidOeffner, JohannesJohannesOeffner2025-11-242025-11-242025-10-018th International Conference on Maritime Autonomous Surface Ships, ICMASS 2025 & Intelligent and Smart Shipping Symposium, ISSS 2025https://hdl.handle.net/11420/59006Motivated by the SeaClear2.0 Project's aim to clean ports and coastal areas using aerial and marine robotics, this work focuses on the reference generation for autopilots of Uncrewed Surface Vehicles (USVs) deployed in confined areas, such as, rivers, channels, ports or harbours. In the envisioned scenario, a USV must navigate through multiple waypoints, which roughly sketch the intended route. The planned route is based on available chart data and doesn't take in consideration optimality of the route or uncharted obstacles. The study implements a global path planner consisting in an A*algorithm, extendable via Genetic Algorithm (GA), for particular scenarios, where the order of the given waypoints is not enforced. In addition, a kinematics-based path planner using the Line-of-Sight (LoS) algorithm is developed for creating the reference vector for the USV control system. The global path planner and LoS algorithms are tested both in simulation and in sea trials, using a medium-sized USV. For the simulation environment, a digital twin of the USV is used. The sea trials validate the concept in a representative environment. The entire software solution is developed under Robot Operating System 2 (ROS2) framework and implements Guidance Navigation and Control (GNC) architecture, commonly used for autonomous navigation of USVs. The global path planning algorithm efficiently handles multi-waypoint selection and finds the shortest path between each two waypoints while avoiding known static obstacles. Additionally, the LoS algorithm generates reliable references for the vessel's autopilot. The novelty of the proposed solution consists in the usage of meta-heuristic algorithms for solving a discrete optimisation problem and in the integration of nautical chart data within the global path planner. The paper highlights the potential of the robotic solution for maritime applications, beyond the chosen scenario, when coupled with a complete GNC solution.en1742-659620251IOP Publishinghttps://creativecommons.org/licenses/by/4.0/Natural Sciences and Mathematics::510: MathematicsConference Paperhttps://doi.org/10.15480/882.1622510.1088/1742-6596/3123/1/01202310.15480/882.16225Conference Paper