Cartography for cooperative manoeuvres with autonomous land vehicles

This article presents a cartographic system to facilitate cooperative manoeuvres among autonomous vehicles in a well-known environment. The main objective is to design an extended cartographic system to help in the navigation of autonomous vehicles. This system has to allow the vehicles not only to access the reference points needed for navigation, but also noticeable information such as the location and type of traffic signals, the proximity to a crossing, the streets en route, etc. To do this, a hierarchical representation of the information has been chosen, where the information has been stored in two levels. The lower level contains the archives with the Universal Traverse Mercator (UTM) coordinates of the points that define the reference segments to follow. The upper level contains a directed graph with the relational database in which streets, crossings, roundabouts and other points of interest are represented. Using this new system it is possible to know when the vehicle approaches a crossing, what other paths arrive at that crossing, and, should there be other vehicles circulating on those paths and arriving at the crossing, which one has the highest priority. The data obtained from the cartographic system is used by the autonomous vehicles for cooperative manoeuvres.

BR3: a biologically inspired fish-like robot actuated by SMA-based artificial muscles

Los peces son animales, donde en la mayoría de los casos, son considerados como nadadores muy eficientes y con una alta capacidad de maniobra. En general los peces se caracterizan por su capacidad de maniobra, locomoción silencioso, giros y partidas rápidas y viajes de larga distancia. Los estudios han identificado varios tipos de locomoción que los peces usan para generar maniobras y natación constante. A bajas velocidades la mayoría de los peces utilizan sus aletas pares y / o impares para su locomoción, que ofrecen una mayor maniobrabilidad y mejor eficiencia de propulsión. A altas velocidades la locomoción implica el cuerpo y / o aleta caudal porque esto puede lograr un mayor empuje y aceleración. Estas características pueden inspirar el diseo y fabricación de una piel muy flexible, una aleta caudal mórfica y una espina dorsal no articulada con una gran capacidad de maniobra. Esta tesis presenta el desarrollo de un novedoso pez robot bio-inspirado y biomimético llamado BR3, inspirado en la capacidad de maniobra y nado constante de los peces vertebrados. Inspirado por la morfología de los peces Micropterus salmoides o también conocido como lubina negra, el robot BR3 utiliza su fundamento biológico para desarrollar modelos y métodos matemáticos precisos que permiten imitar la locomoción de los peces reales. Los peces Largemouth Bass pueden lograr un nivel increíble de maniobrabilidad y eficacia de la propulsión mediante la combinación de los movimientos ondulatorios y aletas morficas. Para imitar la locomoción de los peces reales en una contraparte artificial se necesita del análisis de tecnologías de actuación alternativos, como arreglos de fibras musculares en lugar de servo actuadores o motores DC estándar, así como un material flexible que proporciona una estructura continua sin juntas. Las aleaciones con memoria de forma (SMAs) proveen la posibilidad de construir robots livianos, que no emiten ruido, sin motores, sin juntas y sin engranajes. Asi es como un pez robot submarino se ha desarrollado y cuyos movimientos son generados mediante SMAs. Estos actuadores son los adecuados para doblar la espina dorsal continua del pez robot, que a su vez provoca un cambio en la curvatura del cuerpo. Este tipo de arreglo estructural está inspirado en los músculos rojos del pescado, que son usados principalmente durante la natación constante para la flexión de una estructura flexible pero casi incompresible como lo es la espina dorsal de pescado. Del mismo modo la aleta caudal se basa en SMAs y se modifica para llevar a cabo el trabajo necesario. La estructura flexible proporciona empuje y permite que el BR3 nade. Por otro lado la aleta caudal mórfica proporciona movimientos de balanceo y guiada. Motivado por la versatilidad del BR3 para imitar todos los modos de natación (anguilliforme, carangiforme, subcarangiforme y tunniforme) se propone un controlador de doblado y velocidad. La ley de control de doblado y velocidad incorpora la información del ángulo de curvatura y de la frecuencia para producir el modo de natación deseado y a su vez controlar la velocidad de natación. Así mismo de acuerdo con el hecho biológico de la influencia de la forma de la aleta caudal en la maniobrabilidad durante la natación constante se propone un control de actitud. Esta novedoso robot pescado es el primero de su tipo en incorporar sólo SMAs para doblar una estructura flexible continua y sin juntas y engranajes para producir empuje e imitar todos los modos de natación, así como la aleta caudal que es capaz de cambiar su forma. Este novedoso diseo mecatrónico presenta un futuro muy prometedor para el diseo de vehículos submarinos capaces de modificar su forma y nadar mas eficientemente. La nueva metodología de control propuesto en esta tesis proporcionan una forma totalmente nueva de control de robots basados en SMAs, haciéndolos energéticamente más eficientes y la incorporación de una aleta caudal mórfica permite realizar maniobras más eficientemente. En su conjunto, el proyecto BR3 consta de cinco grandes etapas de desarrollo: • Estudio y análisis biológico del nado de los peces con el propósito de definir criterios de diseño y control. • Formulación de modelos matemáticos que describan la: i) cinemática del cuerpo, ii) dinámica, iii) hidrodinámica iv) análisis de los modos de vibración y v) actuación usando SMA. Estos modelos permiten estimar la influencia de modular la aleta caudal y el doblado del cuerpo en la producción de fuerzas de empuje y fuerzas de rotación necesarias en las maniobras y optimización del consumo de energía. • Diseño y fabricación de BR3: i) estructura esquelética de la columna vertebral y el cuerpo, ii) mecanismo de actuación basado en SMAs para el cuerpo y la aleta caudal, iii) piel artificial, iv) electrónica embebida y v) fusión sensorial. Está dirigido a desarrollar la plataforma de pez robot BR3 que permite probar los métodos propuestos. • Controlador de nado: compuesto por: i) control de las SMA (modulación de la forma de la aleta caudal y regulación de la actitud) y ii) control de nado continuo (modulación de la velocidad y doblado). Está dirigido a la formulación de los métodos de control adecuados que permiten la modulación adecuada de la aleta caudal y el cuerpo del BR3. • Experimentos: está dirigido a la cuantificación de los efectos de: i) la correcta modulación de la aleta caudal en la producción de rotación y su efecto hidrodinámico durante la maniobra, ii) doblado del cuerpo para la producción de empuje y iii) efecto de la flexibilidad de la piel en la habilidad para doblarse del BR3. También tiene como objetivo demostrar y validar la hipótesis de mejora en la eficiencia de la natación y las maniobras gracias a los nuevos métodos de control presentados en esta tesis. A lo largo del desarrollo de cada una de las cinco etapas, se irán presentando los retos, problemáticas y soluciones a abordar. Los experimentos en canales de agua estarán orientados a discutir y demostrar cómo la aleta caudal y el cuerpo pueden afectar considerablemente la dinámica / hidrodinámica de natación / maniobras y cómo tomar ventaja de la modulación de curvatura que la aleta caudal mórfica y el cuerpo permiten para cambiar correctamente la geometría de la aleta caudal y del cuerpo durante la natación constante y maniobras. ABSTRACT Fishes are animals where in most cases are considered as highly manoeuvrable and effortless swimmers. In general fishes are characterized for his manoeuvring skills, noiseless locomotion, rapid turning, fast starting and long distance cruising. Studies have identified several types of locomotion that fish use to generate maneuvering and steady swimming. At low speeds most fishes uses median and/or paired fins for its locomotion, offering greater maneuverability and better propulsive efficiency At high speeds the locomotion involves the body and/or caudal fin because this can achieve greater thrust and accelerations. This can inspire the design and fabrication of a highly deformable soft artificial skins, morphing caudal fins and non articulated backbone with a significant maneuverability capacity. This thesis presents the development of a novel bio-inspired and biomimetic fishlike robot (BR3) inspired by the maneuverability and steady swimming ability of ray-finned fishes (Actinopterygii, bony fishes). Inspired by the morphology of the Largemouth Bass fish, the BR3 uses its biological foundation to develop accurate mathematical models and methods allowing to mimic fish locomotion. The Largemouth Bass fishes can achieve an amazing level of maneuverability and propulsive efficiency by combining undulatory movements and morphing fins. To mimic the locomotion of the real fishes on an artificial counterpart needs the analysis of alternative actuation technologies more likely muscle fiber arrays instead of standard servomotor actuators as well as a bendable material that provides a continuous structure without joins. The Shape Memory Alloys (SMAs) provide the possibility of building lightweight, joint-less, noise-less, motor-less and gear-less robots. Thus a swimming underwater fish-like robot has been developed whose movements are generated using SMAs. These actuators are suitable for bending the continuous backbone of the fish, which in turn causes a change in the curvature of the body. This type of structural arrangement is inspired by fish red muscles, which are mainly recruited during steady swimming for the bending of a flexible but nearly incompressible structure such as the fishbone. Likewise the caudal fin is based on SMAs and is customized to provide the necessary work out. The bendable structure provides thrust and allows the BR3 to swim. On the other hand the morphing caudal fin provides roll and yaw movements. Motivated by the versatility of the BR3 to mimic all the swimming modes (anguilliform, caranguiform, subcaranguiform and thunniform) a bending-speed controller is proposed. The bending-speed control law incorporates bend angle and frequency information to produce desired swimming mode and swimming speed. Likewise according to the biological fact about the influence of caudal fin shape in the maneuverability during steady swimming an attitude control is proposed. This novel fish robot is the first of its kind to incorporate only SMAs to bend a flexible continuous structure without joints and gears to produce thrust and mimic all the swimming modes as well as the caudal fin to be morphing. This novel mechatronic design is a promising way to design more efficient swimming/morphing underwater vehicles. The novel control methodology proposed in this thesis provide a totally new way of controlling robots based on SMAs, making them more energy efficient and the incorporation of a morphing caudal fin allows to perform more efficient maneuvers. As a whole, the BR3 project consists of five major stages of development: • Study and analysis of biological fish swimming data reported in specialized literature aimed at defining design and control criteria. • Formulation of mathematical models for: i) body kinematics, ii) dynamics, iii) hydrodynamics, iv) free vibration analysis and v) SMA muscle-like actuation. It is aimed at modelling the e ects of modulating caudal fin and body bend into the production of thrust forces for swimming, rotational forces for maneuvering and energy consumption optimisation. • Bio-inspired design and fabrication of: i) skeletal structure of backbone and body, ii) SMA muscle-like mechanisms for the body and caudal fin, iii) the artificial skin, iv) electronics onboard and v) sensor fusion. It is aimed at developing the fish-like platform (BR3) that allows for testing the methods proposed. • The swimming controller: i) control of SMA-muscles (morphing-caudal fin modulation and attitude regulation) and ii) steady swimming control (bend modulation and speed modulation). It is aimed at formulating the proper control methods that allow for the proper modulation of BR3’s caudal fin and body. • Experiments: it is aimed at quantifying the effects of: i) properly caudal fin modulation into hydrodynamics and rotation production for maneuvering, ii) body bending into thrust generation and iii) skin flexibility into BR3 bending ability. It is also aimed at demonstrating and validating the hypothesis of improving swimming and maneuvering efficiency thanks to the novel control methods presented in this thesis. This thesis introduces the challenges and methods to address these stages. Waterchannel experiments will be oriented to discuss and demonstrate how the caudal fin and body can considerably affect the dynamics/hydrodynamics of swimming/maneuvering and how to take advantage of bend modulation that the morphing-caudal fin and body enable to properly change caudal fin and body’ geometry during steady swimming and maneuvering.

Rapid prototyping framework for visual control of autonomous micro aerial vehicles

Rapid prototyping environments can speed up the research of visual control algorithms. We have designed and implemented a software framework for fast prototyping of visual control algorithms for Micro Aerial Vehicles (MAV). We have applied a combination of a proxy-based network communication architecture and a custom Application Programming Interface. This allows multiple experimental configurations, like drone swarms or distributed processing of a drone’s video stream. Currently, the framework supports a low-cost MAV: the Parrot AR.Drone. Real tests have been performed on this platform and the results show comparatively low figures of the extra communication delay introduced by the framework, while adding new functionalities and flexibility to the selected drone. This implementation is open-source and can be downloaded from www.vision4uav.com/?q=VC4MAV-FW

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.

Autonomous vehicle control systems for safe crossroads

This article presents a cooperative manoeuvre among three dual mode cars – vehicles equipped with sensors and actuators, and that can be driven either manually or autonomously. One vehicle is driven autonomously and the other two are driven manually. The main objective is to test two decision algorithms for priority conflict resolution at intersections so that a vehicle autonomously driven can take their own decision about crossing an intersection mingling with manually driven cars without the need for infrastructure modifications. To do this, the system needs the position, speeds, and turning intentions of the rest of the cars involved in the manoeuvre. This information is acquired via communications, but other methods are also viable, such as artificial vision. The idea of the experiments was to adjust the speed of the manually driven vehicles to force a situation where all three vehicles arrive at an intersection at the same time.

Autonomous Landing of an Unmanned Aerial Vehicle using Image-Based Fuzzy Control

This paper presents a vision based autonomous landing control approach for unmanned aerial vehicles (UAV). The 3D position of an unmanned helicopter is estimated based on the homographies estimated of a known landmark. The translation and altitude estimation of the helicopter against the helipad position are the only information that is used to control the longitudinal, lateral and descend speeds of the vehicle. The control system approach consists in three Fuzzy controllers to manage the speeds of each 3D axis of the aircraft s coordinate system. The 3D position estimation was proven rst, comparing it with the GPS + IMU data with very good results. The robust of the vision algorithm against occlusions was also tested. The excellent behavior of the Fuzzy control approach using the 3D position estimation based in homographies was proved in an outdoors test using a real unmanned helicopter.

A General Purpose Configurable Navigation Controller for Micro Aerial Multirotor Vehicles

In this paper, we consider the problem of autonomous navigation of multirotor platforms in GPS-denied environments. The focus of this work is on safe navigation based on unperfect odometry measurements, such as on-board optical flow measurements. The multirotor platform is modeled as a flying object with specific kinematic constraints that must be taken into account in order to obtain successful results. A navigation controller is proposed featuring a set of configurable parameters that allow, for instance, to have a configuration setup for fast trajectory following, and another to soften the control laws and make the vehicle navigation more precise and slow whenever necessary. The proposed controller has been successfully implemented in two different multirotor platforms with similar sensoring capabilities showing the openness and tolerance of the approach. This research is focused around the Computer Vision Group's objective of applying multirotor vehicles to civilian service applications. The presented work was implemented to compete in the International Micro Air Vehicle Conference and Flight Competition IMAV 2012, gaining two awards: the Special Award on "Best Automatic Performance - IMAV 2012" and the second overall prize in the participating category "Indoor Flight Dynamics - Rotary Wing MAV". Most of the code related to the present work is available as two open-source projects hosted in GitHub.

An Autonomous Engine for Services Configuration and Deployment.

The runtime management of the infrastructure providing service-based systems is a complex task, up to the point where manual operation struggles to be cost effective. As the functionality is provided by a set of dynamically composed distributed services, in order to achieve a management objective multiple operations have to be applied over the distributed elements of the managed infrastructure. Moreover, the manager must cope with the highly heterogeneous characteristics and management interfaces of the runtime resources. With this in mind, this paper proposes to support the configuration and deployment of services with an automated closed control loop. The automation is enabled by the definition of a generic information model, which captures all the information relevant to the management of the services with the same abstractions, describing the runtime elements, service dependencies, and business objectives. On top of that, a technique based on satisfiability is described which automatically diagnoses the state of the managed environment and obtains the required changes for correcting it (e.g., installation, service binding, update, or configuration). The results from a set of case studies extracted from the banking domain are provided to validate the feasibility of this proposa

Vision-based vehicle detection and tracking with a mobile camera using a statistical framework

En esta tesis se aborda la detección y el seguimiento automático de vehículos mediante técnicas de visión artificial con una cámara monocular embarcada. Este problema ha suscitado un gran interés por parte de la industria automovilística y de la comunidad científica ya que supone el primer paso en aras de la ayuda a la conducción, la prevención de accidentes y, en última instancia, la conducción automática. A pesar de que se le ha dedicado mucho esfuerzo en los últimos años, de momento no se ha encontrado ninguna solución completamente satisfactoria y por lo tanto continúa siendo un tema de investigación abierto. Los principales problemas que plantean la detección y seguimiento mediante visión artificial son la gran variabilidad entre vehículos, un fondo que cambia dinámicamente debido al movimiento de la cámara, y la necesidad de operar en tiempo real. En este contexto, esta tesis propone un marco unificado para la detección y seguimiento de vehículos que afronta los problemas descritos mediante un enfoque estadístico. El marco se compone de tres grandes bloques, i.e., generación de hipótesis, verificación de hipótesis, y seguimiento de vehículos, que se llevan a cabo de manera secuencial. No obstante, se potencia el intercambio de información entre los diferentes bloques con objeto de obtener el máximo grado posible de adaptación a cambios en el entorno y de reducir el coste computacional. Para abordar la primera tarea de generación de hipótesis, se proponen dos métodos complementarios basados respectivamente en el análisis de la apariencia y la geometría de la escena. Para ello resulta especialmente interesante el uso de un dominio transformado en el que se elimina la perspectiva de la imagen original, puesto que este dominio permite una búsqueda rápida dentro de la imagen y por tanto una generación eficiente de hipótesis de localización de los vehículos. Los candidatos finales se obtienen por medio de un marco colaborativo entre el dominio original y el dominio transformado. Para la verificación de hipótesis se adopta un método de aprendizaje supervisado. Así, se evalúan algunos de los métodos de extracción de características más populares y se proponen nuevos descriptores con arreglo al conocimiento de la apariencia de los vehículos. Para evaluar la efectividad en la tarea de clasificación de estos descriptores, y dado que no existen bases de datos públicas que se adapten al problema descrito, se ha generado una nueva base de datos sobre la que se han realizado pruebas masivas. Finalmente, se presenta una metodología para la fusión de los diferentes clasificadores y se plantea una discusión sobre las combinaciones que ofrecen los mejores resultados. El núcleo del marco propuesto está constituido por un método Bayesiano de seguimiento basado en filtros de partículas. Se plantean contribuciones en los tres elementos fundamentales de estos filtros: el algoritmo de inferencia, el modelo dinámico y el modelo de observación. En concreto, se propone el uso de un método de muestreo basado en MCMC que evita el elevado coste computacional de los filtros de partículas tradicionales y por consiguiente permite que el modelado conjunto de múltiples vehículos sea computacionalmente viable. Por otra parte, el dominio transformado mencionado anteriormente permite la definición de un modelo dinámico de velocidad constante ya que se preserva el movimiento suave de los vehículos en autopistas. Por último, se propone un modelo de observación que integra diferentes características. En particular, además de la apariencia de los vehículos, el modelo tiene en cuenta también toda la información recibida de los bloques de procesamiento previos. El método propuesto se ejecuta en tiempo real en un ordenador de propósito general y da unos resultados sobresalientes en comparación con los métodos tradicionales. ABSTRACT This thesis addresses on-road vehicle detection and tracking with a monocular vision system. This problem has attracted the attention of the automotive industry and the research community as it is the first step for driver assistance and collision avoidance systems and for eventual autonomous driving. Although many effort has been devoted to address it in recent years, no satisfactory solution has yet been devised and thus it is an active research issue. The main challenges for vision-based vehicle detection and tracking are the high variability among vehicles, the dynamically changing background due to camera motion and the real-time processing requirement. In this thesis, a unified approach using statistical methods is presented for vehicle detection and tracking that tackles these issues. The approach is divided into three primary tasks, i.e., vehicle hypothesis generation, hypothesis verification, and vehicle tracking, which are performed sequentially. Nevertheless, the exchange of information between processing blocks is fostered so that the maximum degree of adaptation to changes in the environment can be achieved and the computational cost is alleviated. Two complementary strategies are proposed to address the first task, i.e., hypothesis generation, based respectively on appearance and geometry analysis. To this end, the use of a rectified domain in which the perspective is removed from the original image is especially interesting, as it allows for fast image scanning and coarse hypothesis generation. The final vehicle candidates are produced using a collaborative framework between the original and the rectified domains. A supervised classification strategy is adopted for the verification of the hypothesized vehicle locations. In particular, state-of-the-art methods for feature extraction are evaluated and new descriptors are proposed by exploiting the knowledge on vehicle appearance. Due to the lack of appropriate public databases, a new database is generated and the classification performance of the descriptors is extensively tested on it. Finally, a methodology for the fusion of the different classifiers is presented and the best combinations are discussed. The core of the proposed approach is a Bayesian tracking framework using particle filters. Contributions are made on its three key elements: the inference algorithm, the dynamic model and the observation model. In particular, the use of a Markov chain Monte Carlo method is proposed for sampling, which circumvents the exponential complexity increase of traditional particle filters thus making joint multiple vehicle tracking affordable. On the other hand, the aforementioned rectified domain allows for the definition of a constant-velocity dynamic model since it preserves the smooth motion of vehicles in highways. Finally, a multiple-cue observation model is proposed that not only accounts for vehicle appearance but also integrates the available information from the analysis in the previous blocks. The proposed approach is proven to run near real-time in a general purpose PC and to deliver outstanding results compared to traditional methods.

Improving Speech Interaction in Vehicles Using Context-Aware Information through A SCXML Framework

Speech Technologies can provide important benefits for the development of more usable and safe in-vehicle human-machine interactive systems (HMIs). However mainly due robustness issues, the use of spoken interaction can entail important distractions to the driver. In this challenging scenario, while speech technologies are evolving, further research is necessary to explore how they can be complemented with both other modalities (multimodality) and information from the increasing number of available sensors (context-awareness). The perceived quality of speech technologies can significantly be increased by implementing such policies, which simply try to make the best use of all the available resources; and the in vehicle scenario is an excellent test-bed for this kind of initiatives. In this contribution we propose an event-based HMI design framework which combines context modelling and multimodal interaction using a W3C XML language known as SCXML. SCXML provides a general process control mechanism that is being considered by W3C to improve both voice interaction (VoiceXML) and multimodal interaction (MMI). In our approach we try to anticipate and extend these initiatives presenting a flexible SCXML-based approach for the design of a wide range of multimodal context-aware HMI in-vehicle interfaces. The proposed framework for HMI design and specification has been implemented in an automotive OSGi service platform, and it is being used and tested in the Spanish research project MARTA for the development of several in-vehicle interactive applications.

Engineering an Ontology for Autonomous Systems - The OASys Ontology

This paper describes the development of an ontology for autonomous systems, as the initial stage of a research programe on autonomous systems’ engineering within a model-based control approach. The ontology aims at providing a unified conceptual framework for the autonomous systems’ stakeholders, from developers to software engineers. The modular ontology contains both generic and domain-specific concepts for autonomous systems description and engineering. The ontology serves as the basis in a methodology to obtain the autonomous system’s conceptual models. The objective is to obtain and to use these models as main input for the autonomous system’s model-based control system.

3D Object following based on visual information for Unmanned Aerial Vehicles

This article presents a novel system and a control strategy for visual following of a 3D moving object by an Unmanned Aerial Vehicle UAV. The presented strategy is based only on the visual information given by an adaptive tracking method based on the color information, which jointly with the dynamics of a camera fixed to a rotary wind UAV are used to develop an Image-based visual servoing IBVS system. This system is focused on continuously following a 3D moving target object, maintaining it with a fixed distance and centered on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigation

Precision Agriculture without borders: Practical issues and improvements in farmland coverage with aerial vehicles.

This work presents a solution for the aerial coverage of a field by using a fleet of aerial vehicles. The use of Unmanned Aerial Vehicles allows to obtain high resolution mosaics to be used in Precision Agriculture techniques. This report is focus on providing a solution for the full simultaneous coverage problem taking into account restrictions as the required spatial resolution and overlap while maintaining similar light conditions and safety operation of the drones. Results obtained from real field tests are finally reported

Safety assessment of underground vehicles passing over highly resilient straight tracks in the presence of a broken rail

In this paper, vehicle-track interaction for a new slab track design, conceived to reduce noise and vibration levels has been analyzed, assessing the derailment risk for trains running on curved track when encountering a broken rail. Two different types of rail fastening systems with different elasticities have been analysed and compared. Numerical methods were used in order to simulate the dynamic behaviour of the train-track interaction. Multibody system (MBS) modelling techniques were combined with techniques based on the finite element method (FEM). MBS modelling was used for modelling the vehicle and FEM for simulating the elastic track. The simulation model was validated by comparing simulated results to experimental data obtained in field testing. During the simulations various safety indices, characteristic of derailment risk, were analysed. The simulations realised at the maximum running velocity of 110 km/h showed a similar behaviour for several track types. When reducing the running speed, the safety indices worsened for both cases. Although the worst behaviour was observed for the track with a greater elasticity, in none of the simulations did a derailment occur when running over the broken rail.