No abstract

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.

Six-degree-of-freedom (6-DoF) pose estimation is of fundamental importance to many applications, such as robotics, indoor tracking and Augmented Reality. Although a number of pose estimation solutions have been proposed, it remains a critical challenge to provide a low-cost, real-time, accurate and easy-todeploy solution. Addressing this issue, this paper describes a multisensor system for accurate pose estimation that relies on low-cost technologies, in particular on a combination of webcams, inertial sensors and a printable colored fiducial. With the aid of inertial sensors, the system can estimate full pose both with monocular and stereo vision. The system error propagation is analyzed and validated by simulations and experimental tests. Our error analysis and experimental data demonstrate that the proposed system has great potential in practical applications, as it achieves high accuracy (in the order of centimeters for the position estimation and few degrees for the orientation estimation) using the mentioned low-cost sensors, while satisfying tight real-time requirements.

No abstract

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.