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

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.