SOURCE-LINKED INTELLIGENCE
Marine Autonomous Vehicle Fleet Scheduling to Maximise Scientific Impact
The marine science community increasingly relies on Marine Autonomous Vehicles (MAVs) to collect the critical environmental data required to understand global ocean systems. However, as these operations scale, manually routing and planning large autonomous fleets becomes exponentially complex and time-consuming. To address this, we propose a mixed-integer linear programming (MILP) model designed to automate and optimise MAV deployment schedules. The model accounts for strict operational constraints, including battery capacities and time windows for data collection, while aiming to maximise tot
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-27T15:49:49.000Z
First collected: 2026-09-21T08:32:02.028Z. This is not the publication date.