Telecommunication Information Technology (TIT)

Genetic Algorithm-Based Approaches for Enhancing Multi-UAV Route Planning



This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.


1. Introduction
2. Improvement of multi-UAV route planning method based on genetic algorithm
2.1 Foresighted approach
2.2 Multi-step
3. Simulation experiment and result analysis
Limitations and Challenges


  • Mohammed Abdulhakim Al-Absi Dr, Department of Computer Engineering, Dongseo University, Busan, Korea
  • Hoon Jae Lee Professor, Dongseo University, Division of Information and Communication Engineering, Korea
  • Young-sil Lee Associate Professor, International College, Dongseo University, Busan, Korea


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