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Related Experiment Video

Updated: Nov 17, 2025

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Energy-Efficient Swarming Flight Formation Transitions Using the Improved Fair Hungarian Algorithm.

SungTae Moon1,2, Donghun Lee3, Dongoo Lee2

  • 1Aerospace Systems and Control Laboratory, Korea Advanced Institute of Science and Technology (KAIST), Deajon 34141, Korea.

Sensors (Basel, Switzerland)
|February 13, 2021
PubMed
Summary
This summary is machine-generated.

Drone show operating time is extended by minimizing scene transition time and avoiding collisions. A new algorithm reduces drone movement distance and uses multilayer methods for energy efficiency and safety.

Keywords:
Hungarian algorithmRTK-GPSswarming flight system

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Area of Science:

  • Robotics
  • Computer Science
  • Aerospace Engineering

Background:

  • Drone shows offer impressive visual displays through the integration of technology and art.
  • Limited battery life restricts the operational duration of drone performances.
  • Minimizing transition time between scenes is crucial for extending drone show playtime.

Purpose of the Study:

  • To develop a fast and energy-efficient algorithm for minimizing scene transition times in drone shows.
  • To increase the overall operating time of drone performances by reducing unnecessary movement.
  • To ensure collision avoidance between drones during transitions.

Main Methods:

  • A novel scene transition algorithm was designed to minimize drone movement distance.
  • A multilayer approach was implemented for effective collision avoidance among drones.
  • A swarming flight system with robust communication and position estimation was developed for experimental validation.

Main Results:

  • The proposed algorithm successfully minimized transition times between scenes.
  • The algorithm demonstrated energy efficiency by reducing maximum drone movement distances.
  • The multilayer collision avoidance system proved effective in a large-scale drone show.

Conclusions:

  • The developed algorithm significantly enhances drone show efficiency and duration.
  • The integration of the algorithm with a swarming flight system provides a practical solution for real-world applications.
  • This research contributes to advancing the capabilities and performance of autonomous drone systems.