A Hybrid Control Approach for the Swing Free Transportation of a Double Pendulum with a Quadrotor

In this article, a control strategy approach is proposed for a system consisting of a quadrotor transporting a double pendulum. In our case, we attempt to achieve a swing free transportation of the pendulum, while the quadrotor closely follows a specific trajectory. This dynamic system is highly nonlinear, therefore, the fulfillment of this complex task represents a demanding challenge. Moreover, achieving dampening of the double pendulum oscillations while following a precise trajectory are conflicting goals. We apply a proportional derivative (PD) and a model predictive control (MPC) controllers for this task. Transportation of a multiple pendulum with an aerial robot is a step forward in the state of art towards the study of the transportation of loads with complex dynamics. We provide the modeling of the quadrotor and the double pendulum. For MPC we define the cost function that has to be minimized to achieve optimal control. We report encouraging positive results on a simulated environmentcomparing the performance of our MPC-PD control circuit against a PD-PD configuration, achieving a three fold reduction of the double pendulum maximum swinging angle.This work has been partially supported by FEDER funds through MINECO project TIN2017-85827-P, and project KK-202000044 of the Elkartek 2020 funding program of the Basque Government. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 777720

Hybrid Modeling of Deformable Linear Objects for Their Cooperative Transportation by Teams of Quadrotors

his paper deals with the control of a team of unmanned air vehicles (UAVs), specifically quadrotors, for which their mission is the transportation of a deformable linear object (DLO), i.e., a cable, hose or similar object in quasi-stationary state, while cruising towards destination. Such missions have strong industrial applications in the transportation of hoses or power cables to specific locations, such as the emergency power or water supply in hazard situations such as fires or earthquake damaged structures. This control must be robust to withstand strong and sudden wind disturbances and remain stable after aggressive maneuvers, i.e., sharp changes of direction or acceleration. To cope with these, we have previously developed the online adaptation of the proportional derivative (PD) controllers of the quadrotors thrusters, implemented by a fuzzy logic rule system that experienced adaptation by a stochastic gradient rule. However, sagging conditions appearing when the transporting drones are too close or too far away induce singularities in the DLO catenary models, breaking apart the control system. The paper’s main contribution is the formulation of the hybrid selective model of the DLO sections as either catenaries or parabolas, which allows us to overcome these sagging conditions. We provide the specific decision rule to shift between DLO models. Simulation results demonstrate the performance of the proposed approach under stringent conditions.This work has been partially supported by spanish MICIN project PID2020-116346GB-I00, and project KK-2021/00070 of the Elkartek 2021 funding program of the Basque Government. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 777720

Software Architecture for Autonomous and Coordinated Navigation of UAV Swarms in Forest and Urban Firefighting

Advances in the field of unmanned aerial vehicles (UAVs) have led to an exponential increase in their market, thanks to the development of innovative technological solutions aimed at a wide range of applications and services, such as emergencies and those related to fires. In addition, the expansion of this market has been accompanied by the birth and growth of the so-called UAV swarms. Currently, the expansion of these systems is due to their properties in terms of robustness, versatility, and efficiency. Along with these properties there is an aspect, which is still a field of study, such as autonomous and cooperative navigation of these swarms. In this paper we present an architecture that includes a set of complementary methods that allow the establishment of different control layers to enable the autonomous and cooperative navigation of a swarm of UAVs. Among the different layers, there are a global trajectory planner based on sampling, algorithms for obstacle detection and avoidance, and methods for autonomous decision making based on deep reinforcement learning. The paper shows satisfactory results for a line-of-sight based algorithm for global path planner trajectory smoothing in 2D and 3D. In addition, a novel method for autonomous navigation of UAVs based on deep reinforcement learning is shown, which has been tested in 2 different simulation environments with promising results about the use of these techniques to achieve autonomous navigation of UAVs.This work was supported by the Comunidad de Madrid Government through the Industrial Doctorates Grants (GRANT IND2017/TIC-7834)

A vision-based navigation system for Unmanned Aerial Vehicles (UAVs)

The advances in microelectronics foster the Unmanned Aerial Vehicles (UAVs) to be used in many civil and academic applications that require higher levels of autonomy and flight stabilization. The main objective in this paper is to provide UAVs with a robust navigation system; in order to allow the UAVs to perform complex tasks autonomously and in real-time. The proposed algorithms deal with solving the navigation problem for outdoor and indoor environments, mainly based on visual information that is captured by monocular cameras. This paper covers the topics of Pose Estimation, Navigation Guidance, and Visual Servoing. All the proposed algorithms have been verified with real flights in both indoor and outdoor environments, taking into consideration the visual conditions; such as illumination and textures. The obtained results have been validated against other systems; such as VICON motion capture system, DGPS in the case of pose estimate algorithm. In addition, the proposed algorithms have been compared with several previous works in the state of the art, and the results prove the improvement in the accuracy and the robustness of the proposed algorithms.Research supported by the Spanish Government through the CICYT projects (TRA2015-63708-R and TRA2016-78886-C3-1-R), and the Comunidad de Madrid through SEGVAUTO-TRIES (S2013/MIT- 2713). Also, we gratefully acknowledge the support of NVIDIA Corporation with the donation of the GPUs used for this research

Arquitectura de software para navegación autónoma y coordinada de enjambres de drones en labores de lucha contra incendios forestales y urbanos

Los progresos alcanzados dentro del área de los Vehículos Aéreos No Tripulados, conocidos comúnmente como drones, han ocasionado un aumento exponencial de su mercado, gracias, principalmente, al desarrollo e implementación de soluciones tecnológicas innovadoras. La capacidad de este tipo de aeronaves de poder embarcar un gran abanico de sensores provoca que, en la actualidad, se oriente el uso de esta tecnología a un amplio conjunto de aplicaciones y servicios, como son las emergencias y, en concreto, aquellas relacionadas con los incendios, tanto forestales como urbanos. La aparición y crecimiento de empresas, como Drone Hopper S.L, cuya labor se destina al diseño y fabricación de drones de alta capacidad de carga y autonomía destinados a la lucha contra el fuego han provocado que dichas plataformas aéreas se posicionen como una potente y eficaz herramienta en el campo de las emergencias y la seguridad. Actualmente, la empresa Drone Hopper se encuentra inmersa en el diseño y desarrollo de la plataforma WILD HOPPER, capaz de trasladar hasta 600 litros de carga útil y realizar maniobras eficaces en labores de extinción de incendios, gracias, en gran parte, a su sistema patentado de liberación de líquidos. Junto a este sistema, los drones fabricados por Drone Hopper, presentan la ventaja de poder realizar trabajos durante la noche, complementando los trabajos de los medios aéreos tradicionales y, en conjunto, superando las limitaciones de otras plataformas aéreas no tripuladas, cuyo uso en trabajos relacionados con los incendios se limitan a la monitorización y vigilancia de áreas de interés. En los últimos años, se ha producido el nacimiento y expansión de los denominados enjambres de drones, o lo que es lo mismo, equipos escalables de varias aeronaves no tripuladas que operan de manera coordinada y que permiten explotar el uso de tecnologías como la desarrollada por la empresa Drone Hopper. Actualmente, la expansión de estos sistemas es fruto del crecimiento en las investigaciones y desarrollos dentro de este campo, ocasionado, principalmente, por las ventajas que presentan los enjambres de drones en términos de robustez, versatilidad y eficacia. La posibilidad de poder desplegar en un mismo área un conjunto de drones que realicen tareas de manera coordinada provoca, en primer lugar, que se disponga de una herramienta robusta contra averías, en la que la pérdida de cualquiera de los drones intervinientes en la misión no implicaría el fracaso de la misma. Y, en segundo lugar, que se establezca una actuación eficaz ligada a la reducción del tiempo de respuesta y, a la posibilidad de acometer diferentes tareas de manera simultánea. Junto a esto, destacar que el enjambre de drones no está únicamente relacionado al uso de aeronaves no tripuladas con similares características, sino que existe la posibilidad de emplear equipos heterogéneos de drones, o lo que es lo mismo, desplegar sobre un mismo escenario drones con diferentes características, tanto a nivel estructural como de carga de pago, lo que origina que se disponga de una herramienta tecnológica de alta versatilidad. Estas tres características convierten a los enjambres de drones en una herramienta tecnológica de alto valor añadido en trabajos relacionados con la lucha contra el fuego, los cuales se caracterizan por el dinamismo, la adversidad, condiciones extremas y rápidamente cambiantes, en las que el uso de sistemas robustos y versátiles presentan una alta aplicabilidad. Aunque junto a estas propiedades existe un aspecto, el cual sigue constituyendo un campo de estudio, investigación y desarrollo, como es la navegación autónoma y cooperativa de dichos enjambres, lo que permitiría poder emplear esta tecnología sin supervisión humana en la zona, reduciendo de esta manera el riesgo y exposición de vidas humanas. Por este motivo, a lo largo del presente trabajo se desarrolla e implementa una arquitectura de software multi-capa capaz de permitir la navegación autónoma y coordinada de un enjambre de drones para poder acometer trabajos esenciales en la lucha contra el fuego, tanto en áreas urbanas como forestales. La arquitectura propuesta incluye un conjunto de métodos redundantes y complementarios que permiten establecer diferentes capas de control para permitir la navegación sin supervisión y cooperativa del enjambre. La primera de las capas consiste en un planificador de trayectorias, basado en información del entorno en 2D y en 3D, que permite dotar a la arquitectura de un método eficiente y escalable que genere como solución un conjunto de trayectorias óptimas y seguras para que cada uno de los drones pueda alcanzar una ubicación determinada en el entorno. Junto a la efectividad y la escalabilidad, el método propuesto se caracteriza por ser altamente configurable, la cual permite la generación de trayectorias en diferentes situaciones, entre las que destaca la posibilidad de establecer una solución que permita al enjambre de drones alcanzar un objetivo en cuestión bajo una formación concreta, de cara a realizar labores de extinción de manera más eficaz. La segunda de las capas consta de un gestor de colisiones, formado por diferentes desarrollos y algoritmos, que dotan al enjambre de un sistema de detección y evasión de obstáculos, tanto entre drones del enjambre como con obstáculos presentes en el entorno, que garanticen la navegación segura y libre de colisiones de cada uno de los agentes del enjambre. Por último, la arquitectura de software desarrollada en la presente tesis doctoral busca dotar a cada agente del enjambre de un modelo de toma de decisiones inteligente, el cual permita a cada aeronave, de manera autónoma, escoger una secuencia de acciones que le permita alcanzar un objetivo concreto. Este modelo inteligente de toma de decisiones complementa a todos los métodos de la arquitectura propuesta y, permite, de manera redundante establecer un desarrollo adicional que garantice la navegación autónoma del enjambre en entornos dinámicos. La combinación de estos desarrollos bajo una misma arquitectura provoca el despliegue de una flota de drones capaz de navegar y realizar trabajos de manera autónoma y cooperativa sobre entornos adversos y dinámicos, como es el caso de los incendios. Por tanto, los trabajos y desarrollos de la presente tesis doctoral se centran en crear una herramienta tecnológica de alto valor añadido, a partir del desarrollo de arquitecturas de software embarcadas en un enjambre escalable de drones que, trabajando de manera coordinada, establezca una respuesta rápida, eficiente y robusta al problema de los incendios, tanto forestales como urbanos.The progress achieved in the area of Unmanned Aerial Vehicles, commonly known as drones, has caused an exponential increase in its market, mainly thanks to the development and implementation of innovative technological solutions. The capacity of this type of aircraft to be able to embark on a wide range of sensors means that, at present, the use of this technology is directed at a wide range of applications and services, such as emergencies and, specifically, those related to fires, both forest and urban. The appearance and growth of companies such as Drone Hopper S.L., whose work is aimed at the design and manufacture of high load capacity and autonomy drones for firefighting, has led to these aerial platforms being positioned as a powerful and effective tool in the field of emergencies and security. Currently, Dron Hopper is immersed in the design and development of the WILD HOPPER platform, capable of carrying up to 600 liters of payload and perform effective maneuvers in fire fighting, thanks largely to its patented system of liquid release. Together with the system, the drones manufactured by Drone Hopper have the advantage of being able to carry out work at night, complementing the work of traditional aerial means and, as a whole, overcoming the limitations of other unmanned aerial platforms, whose use in fire-related work is limited to the monitoring and surveillance of areas of interest. In recent years, there has been the birth and expansion of the so-called drone swarms, or what is the same, scalable equipment from various unmanned aircraft that operate in a coordinated manner and that allow the use of technologies such as the one developed by the Drone Hopper company. Currently, the expansion of these systems is the result of the growth in research and development within this field, caused mainly by the advantages that drone swarms present in terms of robustness, versatility, and efficiency. The possibility of being able to deploy in the same area a set of drones that carry out tasks in a coordinated way causes, in the first place, that a robust tool against breakdowns is available, in which the loss of any of the drones involved in the mission would not imply the failure of the same one. And, secondly, that an effective action is established, linked to the reduction of the response time and to the possibility of undertaking different tasks simultaneously. In addition to this, it is important to point out that the swarm of drones is not only related to the use of unmanned aircraft with similar characteristics, but that there is also the possibility of using heterogeneous drone teams, or what is the same, deploying drones with different characteristics on the same stage, both at a structural and payload level, which results in a highly versatile technological tool. These three characteristics make drone swarms a high value-added technological tool in firefighting related work, which is characterized by dynamism, adversity, extreme and rapidly changing conditions, in which the use of robust and versatile systems have high applicability. Although together with these properties there is an aspect, which continues to be a field of study, research, and development, as is the autonomous and cooperative navigation of these swarms, which would allow the use of this technology without human supervision in the area, thus reducing the risk and exposure of human lives. For this reason, throughout the present work, multi-layer software architecture is developed and implemented that is capable of allowing the autonomous and coordinated navigation of a swarm of drones to be able to undertake essential fire-fighting work, both in urban and forest areas. The proposed architecture includes a set of redundant and complementary methods that allow establishing different control layers to enable unsupervised and cooperative navigation of the swarm. The first layer consists of a path planner, based on 2D and 3D environmental information, which provides the architecture with an efficient and scalable method that generates a set of optimal and safe paths as a solution so that each of the drones can reach a particular location in the environment. Along with the effectiveness and scalability, the proposed method is characterized by being highly configurable, which allows the generation of trajectories in different situations, among which highlights the possibility of establishing a solution that allows the swarm of drones to reach a target in question under a specific training, to perform extinction work more effectively. The second of the layers consists of a collision manager, formed by different developments and algorithms, which provide the swarm with a system for detecting and avoiding obstacles, both between drones of the swarm and with obstacles present in the environment, to ensure safe and collision-free navigation of each of the agents of the swarm. Finally, the software architecture developed in this doctoral thesis seeks to provide each swarm agent with an intelligent decision-making model, which allows each aircraft, autonomously, to choose a sequence of actions that will allow it to reach a speciffic objective. This intelligent decision-making model complements all the methods of the proposed architecture and, redundantly, allows the establishment of additional development that guarantees the autonomous navigation of the swarm in dynamic environments. The combination of these developments under the same architecture results in the deployment of a fleet of drones capable of navigating and working autonomously and cooperatively in adverse and dynamic environments, such as fires. Therefore, the work and developments of this doctoral thesis are focused on creating a technological tool with high added value, from the development of software architectures embedded in a scalable swarm of drones that, working in a coordinated manner, establish a rapid, efficient and robust response to the problem of fires, both forest and urban.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Pascual Campoy Cervera.- Secretario: Javier Fernández Andrés.- Vocal: Walterio W. Mayol-Cueva