Multi-objective genetic algorithm for civil UAV path planning using 3G communication networks

Fan Hsun Tseng, Cho Hsuan Lee, Li Der Chou, Han Chieh Chao

Research output: Contribution to journalArticlepeer-review


Unmanned Aerial Vehicles (UAVs) have been extensively applied to various applications, such as military aircraft exploration, image transmission for dangerous terrain, relief of disaster. In general, civil UAVs utilize satellite, Global Positioning System, Wi-Fi or the third generation of mobile telecommunications (3G) for data transmission. However, the transmission range of above-mentioned communication technologies limits the flight route of civil UAVs. In this paper, we utilize 3G communication networks for data transmission of civil UAVs. We proposed the multi-objective Genetic algorithm (Moga) to maximize received signal strength and minimize the path length of flight route. In our simulation-based analysis, the proposed Moga is superior to the previous proposed signal-greedy and path-greedy algorithms. The simulation results show that the proposed Moga yields the 1.32 and 3.22 times better signal quality compared to signal-greedy and path-greedy algorithms.

Original languageEnglish
Pages (from-to)26-37
Number of pages12
JournalJournal of Computers (Taiwan)
Issue number6
StatePublished - Dec 2017


  • 3G
  • Civil unmanned aerial vehicle
  • Genetic algorithm
  • Multi-objective optimization
  • Path planning


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