Diseño de un sistema para el manejo a distancia de aeronaves construidas con arduino

El principal objetivo del proyecto es intentar reducir los costes de algunas de las operaciones de vigilancia llevadas a cabo por agencias o instituciones de seguridad. El proyecto consiste en diseñar y desarrollar un sistema informático que permita el manejo a distancia de un cuadricóptero a través de un ordenador, utilizando el teclado y visualizando las imágenes recibidas del módulo de la videocámara. Cada cuadricóptero estará compuesto de diferentes módulos y cada módulo tiene una funcionalidad característica. Se desarrollará un sistema de gestión de aeronaves para poder añadir nuevas unidades de cuadricópteros, así como un sistema de gestión de usuarios para administrar los usuarios en el sistema. Adicionalmente, se construirá un prototipo de cuadricóptero y se implementará su unidad controladora para poder realizar las pruebas del sistema desarrollado con ello. ---ABSTRACT---The aim of this project is to attempt to reduce the costs of some surveillance services offered by security agencies or institutions. The project consists in designing and developing a computer system to remotely control a drone or quad-copter through a computer, manipulating the drone through the keyboard and watching the images captured from the camera module. Each drone is built with one or more modules, and each module has its own functionality. Both new drones and new users can be added to the computer system through the drone management system and the user management system, respectively. Both of management systems are going to be developed. The project also includes the making of a quad-copter prototype and a controller unit implementation.

Isolation in Synchronized Drone Formations

This paper expands on a theoretical model that is used for aerial robots that are working cooperatively to complete a task. In certain situations, such as when multiple robots have catastrophic failures, the surviving robots could become isolated so that they never again communicate with another robot. We prove some properties about isolated robots flying in a grid formation, and we present an algorithm that determines how many robots need to fail to isolate at least one robot. Finally, we propose a strategy that eliminates the possibility of isolation altogether.

Sistema de rádio comunicações para UAV

Os veículos aéreos não tripulados, mais conhecidos por drones, têm tomado atualmente uma posição importante na sociedade. Para além da sua importância no meio militar, têm sido cada vez mais utilizados para meios comerciais uma vez que o seu custo é relativamente baixo e podem ser utilizados para inúmeras aplicações. Devido à sua importância em missões de salvamento, reconhecimento de terreno e até mesmo de ataque, é fundamental uma boa comunicação entre a aeronave e a estação terrestre. Sendo a antena um dos principais elementos do sistema de comunicação, esta dissertação centrou-se no desenvolvimento de uma agregado de antenas a operar à frequência de 2.45GHz. Pretende-se que este agregado apresente polarização circular direita bem como um ganho e largura de banda elevados. Com o objetivo de se obter uma comunicação mais eficiente entre a aeronave e a estação terrestre, o agregado permitirá o redirecionamento do feixe principal do diagrama de radiação. Para tal, serão analisadas três abordagens distintas recorrendo a linhas de atraso e switches, permitindo que seja efetuado beamforming.

Diseño y uso de una paleta háptica para prácticas de teleoperación con simulink

En este artículo se presenta el uso de dispositivos de realimentación de fuerzas de un grado de libertad como herramienta para el desarrollo de aplicaciones docentes en asignaturas de teleoperación y telerrobótica, con el objetivo de disponer de una interfaz física que pueda ser utilizada como equipo de prácticas. Estos dispositivos, conocidos como haptic paddle, ya han sido probados satisfactoriamente para aplicaciones educativas de modelado y simulación de sistemas, ntroducción a los haptics e ingeniería de control en diversas Universidades. Para el desarrollo de los experimentos que se muestran en este artículo se han utilizado dos dispositivos haptic paddle con un controlador basado en Arduino y fabricados mediante tecnologías aditivas de impresión 3D. Gracias a los sensores de fuerza y posición incorporados se pueden implementar esquemas bilaterales de teleoperación de posicón-posición y fuerza-posición.

Experimentally and coupled CFD/CSD assisted structural and aeroelastic modelling of the Javelin UAV outboard wing section

This study presents the procedure followed to make a prediction of the critical flutter speed for a composite UAV wing. At the beginning of the study, there was no information available on the materials used for the construction of the wing, and the wing internal structure was unknown. Ground vibration tests were performed in order to detect the structure’s natural frequencies and mode shapes. From tests, it was found that the wing possesses a high stiffness, presenting well separated first bending and torsional natural frequencies. Two finite element models were developed and matched to experimental results. It has been necessary to introduce some assumptions, due to the uncertainties regarding the structure. The matching process was based on natural frequencies’ sensitivity with respect to a change in the mechanical properties of the materials. Once experimental results were met, average material properties were also found. Aerodynamic coefficients for the wing were obtained by means of a CFD software. The same analysis was also conducted when the wing is deformed in its first four mode shapes. A first approximation for flutter critical speed was made with the classical V - g technique. Finally, wing’s aeroelastic behavior was simulated using a coupled CFD/CSD method, obtaining a more accurate flutter prediction. The CSD solver is based on the time integration of modal dynamic equations, requiring the extraction of mode shapes from the previously performed finite-element analysis. Results show that flutter onset is not a risk for the UAV, occurring at velocities well beyond its operative range.

Neural Network Based UAV Fault Tolerant Control with Aerodynamic Disturbance Estimation and Compensation

In this thesis, the problem of controlling a quadrotor UAV is considered. It is done by presenting an original control system, designed as a combination of Neural Networks and Disturbance Observer, using a composite learning approach for a system of the second order, which is a novel methodology in literature. After a brief introduction about the quadrotors, the concepts needed to understand the controller are presented, such as the main notions of advanced control, the basic structure and design of a Neural Network, the modeling of a quadrotor and its dynamics. The full simulator, developed on the MATLAB Simulink environment, used throughout the whole thesis, is also shown. For the guidance and control purposes, a Sliding Mode Controller, used as a reference, it is firstly introduced, and its theory and implementation on the simulator are illustrated. Finally the original controller is introduced, through its novel formulation, and implementation on the model. The effectiveness and robustness of the two controllers are then proven by extensive simulations in all different conditions of external disturbance and faults.

Trajectory Planning in UAV-Aided Wireless Networks Via Reinforcement Learning

This thesis is focused on the design of a flexible, dynamic and innovative telecommunication's system for future 6G applications on vehicular communications. The system is based on the development of drones acting as mobile base stations in an urban scenario to cope with the increasing traffic demand and avoid network's congestion conditions. In particular, the exploitation of Reinforcement Learning algorithms is used to let the drone learn autonomously how to behave in a scenario full of obstacles with the goal of tracking and serve the maximum number of moving vehicles, by at the same time, minimizing the energy consumed to perform its tasks. This project is an extraordinary opportunity to open the doors to a new way of applying and develop telecommunications in an urban scenario by mixing it to the rising world of the Artificial Intelligence.

Flower cover and bee diversity estimate by drone RGB images

Worldwide, biodiversity is decreasing due to climate change, habitat fragmentation and agricultural intensification. Bees are essential crops pollinator, but their abundance and diversity are decreasing as well. For their conservation, it is necessary to assess the status of bee population. Field data collection methods are expensive and time consuming thus, recently, new methods based on remote sensing are used. In this study we tested the possibility of using flower cover diversity estimated by UAV images (FCD-UAV) to assess bee diversity and abundance in 10 agricultural meadows in the Netherlands. In order to do so, field data of flower and bee diversity and abundance were collected during a campaign in May 2021. Furthermore, RGB images of the areas have been collected using Unmanned Aerial Vehicle (UAV) and post-processed into orthomosaics. Lastly, Random Forest machine learning algorithm was applied to estimate FCD of the species detected in each field. Resulting FCD was expressed with Shannon and Simpson diversity indices, which were successively correlated to bee Shannon and Simpson diversity indices, abundance and species richness. The results showed a positive relationship between FCD-UAV and in-situ collected data about bee diversity, evaluated with Shannon index, abundance and species richness. The strongest relationship was found between FCD (Shannon Index) and bee abundance with R2=0.52. Following, good correlations were found with bee species richness (R2=0.39) and bee diversity (R2=0.37). R2 values of the relationship between FCD (Simpson Index) and bee abundance, species richness and diversity were slightly inferior (0.45, 0.37 and 0.35, respectively). Our results suggest that the proposed method based on the coupling of UAV imagery and machine learning for the assessment of flower species diversity could be developed into valuable tools for large-scale, standardized and cost-effective monitoring of flower cover and of the habitat quality for bees.

Continual learning on nano drones

Miniaturized flying robotic platforms, called nano-drones, have the potential to revolutionize the autonomous robots industry sector thanks to their very small form factor. The nano-drones’ limited payload only allows for a sub-100mW microcontroller unit for the on-board computations. Therefore, traditional computer vision and control algorithms are too computationally expensive to be executed on board these palm-sized robots, and we are forced to rely on artificial intelligence to trade off accuracy in favor of lightweight pipelines for autonomous tasks. However, relying on deep learning exposes us to the problem of generalization since the deployment scenario of a convolutional neural network (CNN) is often composed by different visual cues and different features from those learned during training, leading to poor inference performances. Our objective is to develop and deploy and adaptation algorithm, based on the concept of latent replays, that would allow us to fine-tune a CNN to work in new and diverse deployment scenarios. To do so we start from an existing model for visual human pose estimation, called PULPFrontnet, which is used to identify the pose of a human subject in space through its 4 output variables, and we present the design of our novel adaptation algorithm, which features automatic data gathering and labeling and on-device deployment. We therefore showcase the ability of our algorithm to adapt PULP-Frontnet to new deployment scenarios, improving the R2 scores of the four network outputs, with respect to an unknown environment, from approximately [−0.2, 0.4, 0.0,−0.7] to [0.25, 0.45, 0.2, 0.1]. Finally we demonstrate how it is possible to fine-tune our neural network in real time (i.e., under 76 seconds), using the target parallel ultra-low power GAP 8 System-on-Chip on board the nano-drone, and we show how all adaptation operations can take place using less than 2mWh of energy, a small fraction of the available battery power.

Discovery Of A Rare Pterosaur Bone Bed In A Cretaceous Desert With Insights On Ontogeny And Behavior Of Flying Reptiles.

A pterosaur bone bed with at least 47 individuals (wing spans: 0.65-2.35 m) of a new species is reported from southern Brazil from an interdunal lake deposit of a Cretaceous desert, shedding new light on several biological aspects of those flying reptiles. The material represents a new pterosaur, Caiuajara dobruskii gen. et sp. nov., that is the southermost occurrence of the edentulous clade Tapejaridae (Tapejarinae, Pterodactyloidea) recovered so far. Caiuajara dobruskii differs from all other members of this clade in several cranial features, including the presence of a ventral sagittal bony expansion projected inside the nasoantorbital fenestra, which is formed by the premaxillae; and features of the lower jaw, like a marked rounded depression in the occlusal concavity of the dentary. Ontogenetic variation of Caiuajara dobruskii is mainly reflected in the size and inclination of the premaxillary crest, changing from small and inclined (∼ 115°) in juveniles to large and steep (∼ 90°) in adults. No particular ontogenetic features are observed in postcranial elements. The available information suggests that this species was gregarious, living in colonies, and most likely precocial, being able to fly at a very young age, which might have been a general trend for at least derived pterosaurs.

Unsuccessful attacks dominate a drone-preying wasp's hunting performance near stingless bee nests

Bee males (drones) of stingless bees tend to congregate near entrances of conspecific nests, where they wait for virgin queens that initiate their nuptial flight. We observed that the Neotropical solitary wasp Trachypus boharti (Hymenoptera, Cabronidae) specifically preys on males of the stingless bee Scaptotrigona postica (Hymenoptera, Apidae); these wasps captured up to 50 males per day near the entrance of a single hive. Over 90% of the wasp attacks were unsuccessful; such erroneous attacks often involved conspecific wasps and worker bees. After the capture of non-male prey, wasps almost immediately released these individuals unharmed and continued hunting. A simple behavioral experiment showed that at short distances wasps were not specifically attracted to S. postica males nor were they repelled by workers of the same species. Likely, short-range prey detection near the bees' nest is achieved mainly by vision whereas close-range prey recognition is based principally on chemical and/or mechanical cues. We argue that the dependence on the wasp's visual perception during attack and the crowded and dynamic hunting conditions caused wasps to make many preying attempts that failed. Two wasp-density-related factors, wasp-prey distance and wasp-wasp encounters, may account for the fact that the highest male capture and unsuccessful wasp bee encounter rates occurred at intermediate wasp numbers.