DRONE ROUTING AND TRAJECTORY OPTIMISATION

In recent years, employing Unmanned Aerial Vehicles (UAVs), a.k.a. drones, to collect data has gained popularity. Often, the use of UAVs allows for a reduction in costs for many operations. However, constraints due to the flight dynamics have often been neglected. In this paper we introduce the Unmanned Aerial Vehicle Routing and Trajectory Optimisation Problem (UAVRTOP), the problem of optimising the routes and trajectories of a fleet of UAVs. Motivated by a disaster assessment application, we propose a variant in which a fleet of autonomous aerial gliders is due to photographing a set of waypoints. We propose a Mixed-Integer Non-linear Programming (MINLP) formulation for this variant. In addition, we present a heuristic method that is composed of a novel trajectory optimisation heuristic and a classical routing matheuristic. We perform computational experiments with real-life instances based on flood risk maps of cities in the UK.