System Architectures for Cooperative Teams of Unmanned Aerial Vehicles Interacting Physically with the Environment

Unmanned Aerial Vehicles (UAVs) have become quite a useful tool for a wide range of applications, from inspection & maintenance to search & rescue, among others. The capabilities of a single UAV can be extended or complemented by the deployment of more UAVs, so multi-UAV cooperative teams are becoming a trend. In that case, as di erent autopilots, heterogeneous platforms, and application-dependent software components have to be integrated, multi-UAV system architectures that are fexible and can adapt to the team's needs are required. In this thesis, we develop system architectures for cooperative teams of UAVs, paying special attention to applications that require physical interaction with the environment, which is typically unstructured. First, we implement some layers to abstract the high-level components from the hardware speci cs. Then we propose increasingly advanced architectures, from a single-UAV hierarchical navigation architecture to an architecture for a cooperative team of heterogeneous UAVs. All this work has been thoroughly tested in both simulation and eld experiments in di erent challenging scenarios through research projects and robotics competitions. Most of the applications required physical interaction with the environment, mainly in unstructured outdoors scenarios. All the know-how and lessons learned throughout the process are shared in this thesis, and all relevant code is publicly available.Los vehículos aéreos no tripulados (UAVs, del inglés Unmanned Aerial Vehicles) se han convertido en herramientas muy valiosas para un amplio espectro de aplicaciones, como inspección y mantenimiento, u operaciones de rescate, entre otras. Las capacidades de un único UAV pueden verse extendidas o complementadas al utilizar varios de estos vehículos simultáneamente, por lo que la tendencia actual es el uso de equipos cooperativos con múltiples UAVs. Para ello, es fundamental la integración de diferentes autopilotos, plataformas heterogéneas, y componentes software -que dependen de la aplicación-, por lo que se requieren arquitecturas multi-UAV que sean flexibles y adaptables a las necesidades del equipo. En esta tesis, se desarrollan arquitecturas para equipos cooperativos de UAVs, prestando una especial atención a aplicaciones que requieran de interacción física con el entorno, cuya naturaleza es típicamente no estructurada. Primero se proponen capas para abstraer a los componentes de alto nivel de las particularidades del hardware. Luego se desarrollan arquitecturas cada vez más avanzadas, desde una arquitectura de navegación para un único UAV, hasta una para un equipo cooperativo de UAVs heterogéneos. Todo el trabajo ha sido minuciosamente probado, tanto en simulación como en experimentos reales, en diferentes y complejos escenarios motivados por proyectos de investigación y competiciones de robótica. En la mayoría de las aplicaciones se requería de interacción física con el entorno, que es normalmente un escenario en exteriores no estructurado. A lo largo de la tesis, se comparten todo el conocimiento adquirido y las lecciones aprendidas en el proceso, y el código relevante está publicado como open-source

Unmanned aerial vehicle abstraction layer: An abstraction layer to operate unmanned aerial vehicles

This article presents a software layer to abstract users of unmanned aerial vehicles from the specific hardware of the platform and the autopilot interfaces. The main objective of our unmanned aerial vehicle abstraction layer (UAL) is to simplify the development and testing of higher-level algorithms in aerial robotics by trying to standardize and simplify the interfaces with the unmanned aerial vehicles. Unmanned aerial vehicle abstraction layer supports operation with PX4 and DJI autopilots (among others), which are current leading manufacturers. Besides, unmanned aerial vehicle abstraction layer can work seamlessly with simulated or real platforms and it provides calls to issue standard commands such as taking off, landing or pose, and velocity controls. Even though unmanned aerial vehicle abstraction layer is under continuous development, a stable version is available for public use. We showcase the use of unmanned aerial vehicle abstraction layer with a set of applications coming from several European research projects, where different academic and industrial entities have adopted unmanned aerial vehicle abstraction layer as a common development framework

Urban Air Mobility Market Study

The Booz Allen Team explored market size and potential barriers to Urban Air Mobility (UAM) by focusing on three potential markets – Airport Shuttle, Air Taxi, and Air Ambulance. We found that the Airport Shuttle and Air Taxi markets are viable, with a significant total available market value in the U.S. of $500 billion, for a fully unconstrained scenario. In this unconstrained best-case scenario, passengers would have the ability to access and fly a UAM at any time, from any location to any destination, without being hindered by constraints such as weather, infrastructure, or traffic volume. Significant legal and regulatory, weather, certification, public perception, and infrastructure constraints exist, which reduce the market potential for these applications to only about 0.5$2.5 billion, in the near term. However, we determined that these constraints can be addressed through ongoing intra-governmental partnerships, government and industry collaboration, strong industry commitment, and existing legal and regulatory enablers. We found that the Air Ambulance market is not a viable market if served by electric vertical takeoff and landing (eVTOL) vehicles due to technology constraints but may potentially be viable if a hybrid VTOL aircraft are utilized

Trajectory tracking control of an aerial manipulator in presence of disturbances and modeling uncertainties

Development and dynamic validation of control techniques for trajectory tracking of a robotic manipulator mounted on a UAV. Tracking performances are evaluated in a context of simulated dynamic disturbance on manipulator base

Realisitic VTOL simulator

This master's thesis is focused on the development of a VTOL drone flight simulator. Two main objectives have been set. The first one is that the simulator must simulate all the flight phases of a VTOL. To make it possible, the simulator software is integrated with the simulation of the drone flight controller, which can be ArduPilot or PX4. The second objective is that it should be possible to control the simulated UAV via radio control, in the same way that we would do with a real drone. The thesis is structured in four chapters. In the first chapter, we do a study of the different types of VTOL drones. There are mainly three types: tailsitters, tiltrotors, and QuadPlanes. The three flight phases of a VTOL (vertical take-off and landing, transition and horizontal flight) are also studied. The advantages of a VTOL over a fixed-wing and a multirotor are studied. Finally, we analyse the characteristics of the VTOL that Venturi is developing, called V1. The second chapter summarizes the European laws that affect drones. There are currently two laws: Delegated Regulation 2019/945 and Implementing Regulation 2019/947. The first regulation classifies drones into five classes, according to their capabilities and characteristics. The second regulation deals with the rules and procedures that drones must fulfil. Operations are classified into three categories: open, specific and certified. In the third chapter, a study of the software that is being used for simulation of UAVs is done. The pros and cons of each option are analysed. In view of this study, Gazebo, a robot simulation environment, is chosen for this project. Finally, the last chapter explains the structure of the software that has been developed to carry out the desired simulation. Then, to test this simulator, tests are done with two different QuadPlane models: a model designed by Gazebo and a model of the Venturi V1. Three tests are performed for each of these QuadPlane models: 1) a test of the rotation of the engines and movement of the control surfaces; 2) a test in which the UAV must follow a pre-planned mission; and 3) a test in which we try to control the drone with a joystick. For the first UAV model, the three tests are satisfactory; in particular, the computed average error when following the planned mission is 1.9 m. Moreover, in the joystick control test, the drone responds perfectly to the controls, just like a real VTOL. For the Venturi V1, the first test is satisfactory, but unfortunately the second and third tests cannot be carried out, likely due to an error in the Gazebo model of the V1. As a result of this project, the developed simulator is being integrated in Venturi with a computer vision system for detection of pedestrians, to make safer landings, and for detection of the power lines, so that the UAV can follow them autonomously during power line inspection missions