A Novel Approach to Air Corridor Estimation and Visualization for Autonomous Multi-UAV Flights

Abstract

The world is on the brink of an era of Unmanned Aerial Vehicles (UAVs), widely known to public as drones, where we will get to experience multiple UAVs flying in the national airspace carrying out diverse tasks such as monitoring, surveillance, product deliveries, law enforcement, fertilizing crop fields, aerial photography, and transport. In such scenarios, there is a possibility of collisions, path overlaps, mix-ups, and uncertainties as far as their flying routes are concerned. The routes to which aircraft are restricted to fly are called air corridors. These flying routes could be inside constructed air corridors where the UAVs would be allotted to fly, similar to the air corridors of commercial aircraft. There is a growing need to identify and construct these air corridors for UAVs to fly in their respective corridors to avoid such mishaps. This served as the primary motivation for proposing a novel estimation algorithm and a method to visualize air corridors for autonomous multi-UAV flights in an airspace. In addition, we studied various popular uncertainty visualization techniques to incorporate uncertainty in the visualization of the air corridors. Furthermore, a standalone web application with a user-friendly graphical user interface (GUI) was developed using HTML5, CSS3, JavaScript and CesiumJS. We present the estimation algorithm and related visualization results of our proposed algorithm, and discuss the summarized research findings to conclude this paper.