Mission planning and route optimisation for short-range maritime drones under operational constraints

The rapid advancement of autonomous maritime technologies underscores the growing relevance of optimising delivery operations in coastal and offshore zones, particularly when energy and navigational constraints are present. The aim of this study was to develop a route optimisation model tailored for short range maritime drones operating under limited battery capacity and environmental instability. The methodology involved the formulation of a mathematical model that integrated both distance-dependent propulsion costs and time-dependent navigation overheads, allowing for the minimisation of total mission execution time. Using simulation-based validation, it was established that even short route segments required considerable energy input due to the need for continuous control, stabilisation, and real-time navigation support. The results confirmed the feasibility of applying the model to delivery scenarios with segmented routes and dynamic return to-base strategies. It was demonstrated that exceeding critical energy thresholds on a given segment led to route interruption and reconfiguration, which the model accounts for through embedded constraints and conditional branching logic. Additionally, detailed energy consumption profiles were generated for each route segment, revealing the dominance of navigational overheads in short transitions. The developed model provided a reliable framework for evaluating mission viability before deployment. The practical value of the research lay in its applicability for maritime logistics planners, operators of autonomous surface vehicles, and engineers involved in the deployment of battery-powered maritime delivery systems in nearshore environments