Optimal waypoint assignment for designing drone light show formations

Abstract

Advancements in technology and new drone policies have boosted the adoption of drones by various industries. With active research and development, ingenious applications using drones are being developed. One such innovative and creative application of swarm drones is the drone light show. Light shows are generally performed outdoors in a dedicated clear open air space, which attracts the usage of drones for the execution. A fleet of multiple UAVs illuminates the night sky with picturesque performances in a synchronized manner. Use of drones in light shows provides an eco-friendly and reusable alternative for unique ways of advertisements, celebrations, storytelling, and entertainment. To choreograph the performance of swarm drones means allocating waypoints to each drone for every formation and the complexity of designing increases with the number of drones. An intelligent optimal assignment system is much required to allocate waypoints to drones for each transition in order to create formations. We propose a static swarm-intelligence-based assignment approach named Constrained Hungarian Method for Swarm Drones Assignment (CHungSDA) for optimally assigning multi-UAVs to waypoints. This approach uses Hungarian algorithm as a base with added constraints specific to the targeted application. Several simulations of the proposed approach — carried out for different designs have shown promising results. The work will be of best reference to the UAV manufacturers for their functional design of UAVs and development of Ground Control Station Software to communicate with multiple UAVs, along with other companies that aim to create visual illustrations using UAVs.