Abstract
Recently, drone shows have impressed many people through a convergence of technology and art. However, these demonstrations have limited operating hours based on the battery life. Thus, it is important to minimize the unnecessary transition time between scenes without collision to increase operating time. This paper proposes a fast and energy-efficient scene transition algorithm that minimizes the transition times between scenes. This algorithm reduces the maximum drone movement distance to increase the operating time and exploits a multilayer method to avoid collisions between drones. In addition, a swarming flight system including robust communication and position estimation is presented as a concrete experimental system. The proposed algorithm was verified using the swarming flight system at a drone show performed with 100 drones.
Highlights
As interest in unmanned aerial vehicles (UAVs) increases, many applications utilizing UAVs have been developed in various fields, such as delivery services [1] and reconnaissance
Various studies have been conducted in real environments with simulation [3,4,5]
Intel presented the first successful demonstration with 100 drones, in collaboration with Ars Electronica [10], and later presented a drone show involving more than 1000 drones during the 2018 Pyeongchang Winter Olympics, which was published in the Guinness Book of World Records
Summary
As interest in unmanned aerial vehicles (UAVs) increases, many applications utilizing UAVs have been developed in various fields, such as delivery services [1] and reconnaissance. Most algorithms based on the Hungarian method have attempted to find an optimal solution that minimizes or maximizes the weight or improves the time complexity. A Fair Hungarian algorithm is proposed to generate a scenario that includes transitions between scenes within a short time without collision. (1) To increase the operating time for drone shows, the Fair Hungarian algorithm is proposed to achieve fair energy consumption. The proposed algorithm equalizes the energy demand of the drones by minimizing the maximum movement distance between drones in a swarming flight scenario. Methods to realize efficient communication and reliable position estimation for a swarming flight system are discussed. The emergency control component controls the drones that experience problems during the scenario flight
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