Design and Assessment of Robust Persistent Drone-Based Circular-Trajectory Surveillance Systems
José Luis Andrade-Pineda,
David Canca (),
Marcos Calle,
José Miguel León-Blanco and
Pedro Luis González-R
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José Luis Andrade-Pineda: Robotics, Vision and Control Group, Universidad de Sevilla, 41092 Seville, Spain
David Canca: Department of Industrial Engineering and Management Science, School of Engineering, Universidad de Sevilla, 41092 Seville, Spain
Marcos Calle: Department of Industrial Engineering and Management Science, School of Engineering, Universidad de Sevilla, 41092 Seville, Spain
José Miguel León-Blanco: Department of Industrial Engineering and Management Science, School of Engineering, Universidad de Sevilla, 41092 Seville, Spain
Pedro Luis González-R: Department of Industrial Engineering and Management Science, School of Engineering, Universidad de Sevilla, 41092 Seville, Spain
Mathematics, 2025, vol. 13, issue 8, 1-39
Abstract:
We study the use of a homogeneous fleet of drones to design an unattended persistent drone-based patrolling system for vast circular areas. The drones follow flight missions supported by auxiliary on-ground charging stations, whose location and number must be determined. To this end, we first present a mixed integer non-linear programming model for defining cyclic schedules of drone flights considering the selection of the drone model from a set of candidate drone platforms. By imposing a minimum acceptable time between consecutive visits to any perimeter point, the objective consists of minimizing the total surveillance system deployment cost. The solution provides the best platform, the location of base stations, and the number of drones needed to monitor the perimeter, as well as the flight mission for each drone. We test five commercial platforms in six different scenarios whose radios vary between 1196 and 1696 m. In five of them, the MD4-100 Microdrones model achieves the lower cost solution, with values of EUR 66,800 and 83,500 for Scenarios 1 and 2 and EUR 116,900 for Scenarios 3, 4 and 5, improving its rivals in average percentages that vary between 8.46% and 70.40%. In Scenario number 6, the lower cost solution is provided by the TARTOT-500 model, with a total cost of EUR 168,000, improving by 20% the solution provided by the MD4-100. After obtaining the optimal solution, to evaluate the system robustness, we propose a discrete event simulation model incorporating uncertain flight times taking into account the possibility of accelerated depletion of drones’ Lithium-Ion polymer (Li-Po) batteries. Overall, our research investigates how various factors—such as the number of drones in the fleet and the division of the perimeter into sectors—impact the reliability of the system. Using Scenario number 3, our tests demonstrate that under a risk of battery failures of 2.5% and three UAVs per station, the surveillance system reaches a global percentage of punctually patrolled sectors of 92.6% and limits the number of delayed sectors (the relay UAV reaches the perimeter slightly above the required time, but it positively re-establishes the cyclic pattern for patrolling) to only a 5.6%. Our findings provide valuable insights for designing more robust and cost-effective drone patrol systems capable of operating autonomously over large planning horizons.
Keywords: multi-drone perimeter surveillance; mixed integer non-linear programming; uncertain battery depletion; discrete event simulation; robustness assessment (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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