Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Bio-inspired Evasive Movement of UAVs based on Dragonfly Algorithm in Military Environment

  • Gudi, Siva Leela Krishna Chand (Innovation and Enterprise Research Lab., University of Technology Sydney) ;
  • Kim, Bo-sun (Department of IT Convergence Engineering, Kumoh National Institute of Technology) ;
  • Silvirianti, Silvirianti (Department of IT Convergence Engineering, Kumoh National Institute of Technology) ;
  • Shin, Soo Young (Department of IT Convergence Engineering, Kumoh National Institute of Technology) ;
  • Chae, Seog (Department of IT Convergence Engineering, Kumoh National Institute of Technology)
  • Received : 2018.10.11
  • Accepted : 2019.01.28
  • Published : 2019.03.31
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Abstract

Applications of unmanned aerial vehicles (UAVs) in the military environment have become popular because they require minimum human contribution and can avoid accidents during missions. UAVs are employed in various missions such as reconnaissance, observation, aggression, and protection. Consequently, counter-measures, known as anti-drone technologies, have been developed as well. In order to protect against threats from anti-drone technologies and enhance the survivability of UAVs, this study proposes an evasive measure. The proposed bio-inspired evasive maneuver of a UAV mimics a dragonfly's irregular flight. The unpredictable UAV movement is able to confuse enemies and avoid threats, thereby enhancing the UAV's survivability. The proposed system has been implemented on a commercial UAV platform (AR Drone 2.0) and tested in a real environment. The experiment results demonstrate that the proposed flight pattern has larger displacement values compared to a regular flight maneuver, thus making the UAV's position is difficult to predict.

Keywords

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Fig. 1. Various UAVsc for military purpose [3].

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Fig. 2. Examples of anti-drone technology [5].

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Fig. 3. Dragonfly’s flight pattern.

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Fig. 4. AR drone 2.0.

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Fig. 5. Proposed UAV evasive movement system algorithm.

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Fig. 6. UAV evasive movement control.

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Fig. 7. Key points detected by AR Drone 2.0.

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Fig. 8. Dragonfly-based UAV movement.

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Fig. 9. Flight pattern comparison between dragonfly-based movement and linear movement.

Table 1. AR drone 2.0 specification

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