Development of energy-efficient swarming flight system based on the improved fair hungarian algorithm

Abstract

The increasing interest in drones has generated new application systems in the various areas. Especially, drone shows have impressed many people globally through a convergence of technology and art at the Pyeongchang Winter Olympics. However, this technology is Intel technology, not domestic proprietary technology. in addition, the system including communication and scenario generation has not been revealed because the system was developed privately. The drone show impresses people by expressing various scenes in the sky through the formation of swarming flight. 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. The main contributions of this paper can be summarized as follows: (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. (2) The drone show technology stacked on the veil is discussed. In this paper, methods to realize efficient communication and reliable position estimation for a swarming flight system are discussed. The communication mechanism can operate regardless of the number of drones. The position estimation based on the real time kinematic global positioning system (RTK-GPS) can switch mode smoothly when the RTK-GPS is not used. (3) The algorithm and system are verified through implementation in drone shows involving 100 drones with numerical experiments.