Single-drone energy efficient coverage path planning with multiple charging stations for surveillance




coverage path planning, drone, energy consumption, mathematical model, scenario analysis


Drones have started to be used for surveillance within the cities, visually scanning the predefined zones, quickly detecting abnormal states such as fires, accidents, and pollution, or assessing the disaster zones. Coverage Path Planning (CPP) is a problem that aims to determine the most suitable path or motion plan for a vehicle to cover the entire desired area in the task. So, this paper proposes a novel two-dimensional coverage path planning (CPP) mathematical model with the fact that a single drone may need to be recharged within its route based on its energy consumption, and the obstacles must be avoided while constructing the route. Our study aims to create realistic routes for drones by considering multiple charging stations and obstacles for surveillance. We tested the model for a grid example based on the scenarios obtained by changing the layout, the number of obstacles and recharging stations, and area size using the Python Gurobi Optimization library. As a contribution, we analyzed the impact of the number of existing obstacles and recharging stations, the size and layout of the area to be covered on total energy consumption, and the total solution time of CPP in our study for the first time in the literature, through a detailed Scenario Analysis. Results show that the map size and the number of covered cells affect the total energy consumption, but different layouts with shuffled cells are not effective.  The area size to be covered affects the total computation time, significantly. As the number of obstacles and recharging stations increases, the computation time decreases up to a certain limit, then stabilizes.


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Author Biographies

Atalay Celik, Industrial Engineering Department, Istanbul Technical University, Turkey

Atalay Celik graduated from Istanbul Technical University and earned a bachelor’s degree in Industrial Engineering in 2022. He graduated from the university with a GPA of 3.8 ranked 4th in the department. In the third year of university period, he has been in Delft University of Technology, Netherlands, through the Erasmus Exchange program. He worked on drone coverage path planning optimization problem during his graduation thesis project. Currently, he has been pursuing graduate studies in Big Data and Business Analytics Master’s program, in Istanbul Technical University. He has been also working in TUBITAK BILGEM which is one of the biggest information technology research centers in Türkiye, as a Data Analyst.

Enes Ustaomer, Industrial Engineering Department, Istanbul Technical University, Turkey

Enes Ustaomer has been currently pursuing Big Data & Business Analytics MSc Degree at Istanbul Technical University (ITU). Previously, he completed a Bachelor's Degree in Industrial Engineering at ITU, and was ranked 1st with a 3.91/4.00 GPA. He worked in the defense industry for over two years as an Integrated Logistics Support Analytics Engineer about the technologies such as data analytics, RPA, machine learning, optimization, and text mining. He is mainly focused on optimization, mission route planning, and deep reinforcement algorithms.

Sule Itir Satoglu, Industrial Engineering Department, Istanbul Technical University, Turkey

Sule Itir Satoglu earned her Master’s and PhD degrees from Istanbul Technical University (ITU). She has been working as a professor of Industrial Engineering Department, at ITU. Her research interests include supply chain management and analytics, optimization algorithms, sustainability, and humanitarian logistics in disasters.


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CPP Python Codes



DOI: 10.11121/ijocta.2023.1332
Published: 2023-07-13

How to Cite

Celik, A., Ustaomer, E., & Satoglu, S. I. (2023). Single-drone energy efficient coverage path planning with multiple charging stations for surveillance. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 13(2), 171–180.



Research Articles