# Proactive Mission Planning of Unmanned Aerial Vehicle Fleets Used in Offshore Wind Farm Maintenance  
[PERSON]  
1 Faculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, Poland; [EMAIL_ADDRESS] (Z.B. ); [EMAIL_ADDRESS] (G.R.) [PERSON]  
1 Faculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, Poland; [EMAIL_ADDRESS] (Z.B. ); [EMAIL_ADDRESS] (G.R.) [PERSON]  
2 Department of Materials and Production, Aalborg University, 9220 Aalborg, Denmark; [EMAIL_ADDRESS] (I.N. ); [EMAIL_ADDRESS] (R.F)  
[PERSON]  
2 Department of Materials and Production, Aalborg University, 9220 Aalborg, Denmark; [EMAIL_ADDRESS] (I.N. ); [EMAIL_ADDRESS] (R.F)  
[PERSON]  
1 Faculty of Electronics and Computer Science, Koszalin University of Technology, 75-453 Koszalin, Poland; [EMAIL_ADDRESS] (Z.B. ); [EMAIL_ADDRESS] (G.R.) Footnote 1: [[https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci)]([https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci))  
Footnote 2: [[https://www.mdpi.com/journals/pdf/10/1](https://www.mdpi.com/journals/pdf/10/1)]([https://www.mdpi.com/journals/pdf/10/1](https://www.mdpi.com/journals/pdf/10/1))  
Among the issues dominating OWF maintenance logistics, one can distinguish the issues of vessel route planning and UAV mission planning. Decisions made in these areas influence each other and affect the final costs of WT monitoring/servicing missions. In vessel route planning, a decisive role is played by the choice of vessel route, conditioned by the state of the sea (i.e., maximum allowable significant wave height and peak wave period) and the time taken for a ship to moor at a WT and for the service team to disembark from and return to the vessel. The number of WTs serviced within the planned time window is usually assumed to be its main objective. It is worth adding that both the forecasted weather conditions and daily visibility, conditioned by the year's season, affect this time window [8; 9]. The second issue, UAV mission planning for WT inspection, cleaning, lubrication, and repair, particularly the maintenance of WT main components such as blades, nacelle, and tower, is seeing increasing implementation of UAV technologies because UAVs equipped with a variety of sensors, including ultrasonic, visual, thermographic, and hyperspectral cameras, can detect different types of damage, such as fatigue cracks, surface corrosion, galvanic corrosion, pitting, and stress corrosion cracking [10; 11]. Problems in these areas overlap and permeate to several other problems in the logistics of OWF maintenance. Relevant examples include problems such as hierarchical worker assignment (assuming that an employee with a higher competence can replace a lower-skilled employee by performing assigned tasks in a shorter time), supply chain management (using repair kits to service WTs instead of spare parts, separate from the bullwhip effect), and proactive/reactive O&M planning (taking into account changes in weather forecasts and sea states, as well as considering various emergency scenarios). Such complex, multifaceted problems integrating processes of different natures and characters are difficult to model and even more difficult to solve. They are problems of the NP-hard class [8; 12; 13]. This paper's subject matter references our previous work addressing the issues of proactive and reactive mission planning of a fleet of UAVs carrying out deliveries in changing weather conditions and ad hoc changing sizes and timing of orders. Thus, the studies presented are an attempt to transfer previously gained experience to an environment in which, in addition to atmospheric disturbances, uncertainties caused by the sea's changing state (while conditioning the movement of ships used as mobile UAV bases) are considered.