This paper describes a Mission Definition System and the automated flight process it enables to implement measurement plans for discrete infrastructure inspections using aerial platforms, and specifically multi-rotor drones. The mission definition aims at improving planning efficiency with respect to state-of-the-art waypoint-based techniques, using high-level mission definition primitives and linking them with realistic flight models to simulate the inspection in advance. It also provides flight scripts and measurement plans which can be executed by commercial drones. Its user interfaces facilitate mission definition, pre-flight 3D synthetic mission visualisation and flight evaluation. Results are delivered for a set of representative infrastructure inspection flights, showing the accuracy of the flight prediction tools in actual operations using automated flight control.

Unmanned traffic management (UTM) systems will become a key enabler to the future drone market ecosystem, enabling the safe concurrent operation of both manned and unmanned aircrafts. Currently, these systems are usually tested by performing real scenarios that are costly, limited, hardly scalable, and poorly repeatable. As a solution, in this paper we propose an agent-based simulation platform, implemented through a micro service architecture, which may simulate UTM information sources, such as flight plans, telemetry messages, or tracks from a surveillance network. The final objective of this simulator is to use these information streams to perform a system-level evaluation of UTM systems both in the pre-flight and in-flight stages. The proposed platform, with a focus on simulation of communications and sensors, allows to model UTM actors’ behaviors and their interactions. In addition, it also considers the manual definition of events to simulate unexpected behaviors/events (contingencies), such as communications failures or pilots’ actions. In order to validate our architecture, we implemented a simulator that considers the following actors: drones, pilots, ground control stations, surveillance networks, and communications networks. This platform enables the simulation of the drone trajectory and control, the C2 (command and control) link, drone detection by surveillance sensors, and the communication of all agents by means of a mobile communications network. Our results show that it is possible to truthfully recreate complex scenarios using this simulator, mitigating the disadvantages of real testbeds.

Drone operators, institutions (e.g. law enforcement, rescue agencies, preservation organisms, etc.) and companies (logistics, surveillance, inspection, etc.), are constituting themselves as drone operators, at the same time that increase the size of their fleets of drones. Nowadays, each operator independently manages its drones, on service request. Beyond this isolated approach, many operation scenarios would be much better addressed if automated means for coordinated resource allocation and simultaneous drone control were available. In this paper, we describe a microservice-oriented architecture that provides organization and optimization functionalities to orchestrate drone operation. The platform built on the proposed architecture may be used to enable a single operator to optimize the management of its fleet of drones, but also to facilitate coordination of different resources towards a common goal, assuming a drone-as-a-service operation mode. The architecture is validated through a specific use case, for real time allocation of drone resources to enable fast emergency response.

This paper describes the requirements of a flight planning tool for safe urban operations, which may be used to collaboratively design flights considering traffic constraints and limitations according to an unmanned traffic management system. Representative examples of flight planning are described, as calculated by a prototype flight planning tool.

The large increase in the sale of drones as well as their use in more and more aspects of daily life has led to the emergence of increasingly voices warning of the need to track and monitoring these drones. The prototype UTM monitoring system to be described in this paper is aimed to address this problem. It is implemented as a microservice to be inserted in a complete UTM SW ecosystem, processing telemetry and other sensors position/velocity information to be able to track, monitor and control the good operation and thus avoid the possible conflicts or accidents that can cause due to a bad use or malfunction of them. This prototype may also allow the analysis of the performance without putting at risk neither people nor material goods since all drone data may be simulated. Also, it has been tested using real data from industrial multirotors.