Dissipation rate measurements during R/V Maria S. Merian cruise MSM21/1b dives

GEOMAR's autonomous underwater vehicle (AUV Abyss REMUS 6000) was deployed within the framework of a multi-platform experiment in June 2012 with R/V Maria S. Merian cruise MSM21/1b at about 180 km downstream of Denmark Strait. The scientific payload included a pumped Seabird 49 FastCAT CTD system, a paroscientific pressure sensor, and shear and temperature microstructure profiler from Rockland Scientific Inc.. In total, six of eight AUV dives were carried out successfully. Aborts on three dives were caused by strong counter currents the AUV experienced in the Denmark Strait Overflow plume, which made the AUV fail to reach its waypoints on schedule. During all missions the AUV was programmed to dive at constant depth levels along? straight legs approximately parallel to chosen isobaths with a constant speed of 1.6 m s-1 through the water.

Physical oceanography from R/V Maria S. Merian cruise MSM21/1b dives

GEOMAR's autonomous underwater vehicle (AUV Abyss REMUS 6000) was deployed within the framework of a multi-platform experiment in June 2012 with R/V Maria S. Merian cruise MSM21/1b at about 180 km downstream of Denmark Strait. The scientific payload included a pumped Seabird 49 FastCAT CTD system, a paroscientific pressure sensor, and shear and temperature microstructure profiler from Rockland Scientific Inc.. In total, six of eight AUV dives were carried out successfully. Aborts on three dives were caused by strong counter currents the AUV experienced in the Denmark Strait Overflow plume, which made the AUV fail to reach its waypoints on schedule. During all missions the AUV was programmed to dive at constant depth levels along? straight legs approximately parallel to chosen isobaths with a constant speed of 1.6 m s-1 through the water.

Physical oceanography, current meter data, and microstructure measurements 180 km downstream of Denmark Strait sill during Maria S. Merian cruise MSM21/1b

The main objectives of the cruise MSM21/1b were to characterize the spatio-temporal variability of the Denmark Strait overflow and to identify processes responsible for the exchange of the overflow plume with ambient water downstream of Denmark Strait. A multi-platform approach was taken to achieve the goals, based on moorings, an autonomous underwater vehicle (AUV), as well as lowered and vessel-mounted observations. From these platforms, measurements of temperature, salinity, dissolved oxygen, current velocity, dissipation of turbulent kinetic energy, and bottom pressure were obtained.

Uncalibrated temperature measurement during R/V Maria S. Merian cruise MSM21/1b

GEOMAR's autonomous underwater vehicle (AUV Abyss REMUS 6000) was deployed within the framework of a multi-platform experiment in June 2012 with R/V Maria S. Merian cruise MSM21/1b at about 180 km downstream of Denmark Strait. The scientific payload included a pumped Seabird 49 FastCAT CTD system, a paroscientific pressure sensor, and shear and temperature microstructure profiler from Rockland Scientific Inc.. In total, six of eight AUV dives were carried out successfully. Aborts on three dives were caused by strong counter currents the AUV experienced in the Denmark Strait Overflow plume, which made the AUV fail to reach its waypoints on schedule. During all missions the AUV was programmed to dive at constant depth levels along? straight legs approximately parallel to chosen isobaths with a constant speed of 1.6 m s-1 through the water.

Aerial Object Following Using Visual Fuzzy Servoing

This article presents a visual servoing system to follow a 3D moving object by a Micro Unmanned Aerial Vehicle (MUAV). The presented control strategy is based only on the visual information given by an adaptive tracking method based on the colour information. A visual fuzzy system has been developed for servoing the camera situated on a rotary wing MAUV, that also considers its own dynamics. This system is focused on continuously following of an aerial moving target object, maintaining it with a fixed safe distance and centred 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

Aerodynamic study of airfoils geometric imperfections at low Reynolds number

The interest of this study is based on the observation that some manufacturing processes of various vehicles wings, such as unmanned aerial vehicle (UAV), or blades, such as wind turbine blades, or other devices that use aerodynamic profiles, produce imperfections in the leading edge or open trailing edge with bigger thickness than original airfoil, because, for example, they are manufactured in two parts, top surface and bottom surface and subsequently joined. In this last step might appear a sliding between the top surface and the bottom surface having a small step on the leading edge or a small thickness gain can occur on the trailing edge. Normally these imperfections are corrected through a refill and/or sanding processes using many hours of manual labor. Therefore the initial objective of this research is to determine the level of influence in the aerodynamic characteristics at low Reynolds numbers (Lissaman, 1981, Carmichael, 1981, Nagamatsu and Cuche, 1981, Schmitz, 1957, Cebeci, 1989, Mueller and Batill, 1982) of these imperfections in the manufacture, and determine whether there may be a value for which it would not be necessary to correct them

Towards a ground navigation system based in visual feedback provided by a mini UAV

This paper addresses initial efforts to develop a navigation system for ground vehicles supported by visual feedback from a mini aerial vehicle. A visual-based algorithm computes the ground vehicle pose in the world frame, as well as possible obstacles within the ground vehicle pathway. Relying on that information, a navigation and obstacle avoidance system is used to re-plan the ground vehicle trajectory, ensuring an optimal detour. Finally, some experiments are presented employing a unmanned ground vehicle (UGV) and a low cost mini unmanned aerial vehicle (UAV).

Experimental investigation on box-wing configuration for UAS

The range for airframe configurations available for UAS is as diverse as those used for manned aircraft and more since the commercial risk in trying unorthodox solutions is less for the UAS manufacturer. This is principally because the UAS airframes are usually much smaller than the manned aircraft and operators are less likely to have a bias against unconventional configurations. One of these unconventional configurations is the box-wing, which is an unconventional solution for the design of the new UAS generation. The existence of two wings separated in different planes that are, however, significantly close together, means that the aerodynamic analysis by theoretical or computational methods is a difficult task, due to the considerable interference existing. Considering the fact that the flight of most UAS takes place at low Reynolds numbers, it is necessary to study the aerodynamics of the box wing configuration by testing different models in a wind tunnel to be able to obtain reasonable results. In the present work, the study is enhanced by varying not only the sweepback angles of the two wings, but also their position along the models’ fuselage. Certain models have shown being more efficient than others, pointing out that certain relative positions of wing exists that can improve the aerodynamics efficiency of the box wing configuration.

See-and-avoid quadcopter using fuzzy control optimized by cross-entropy

In this work we present an optimized fuzzy visual servoing system for obstacle avoidance using an unmanned aerial vehicle. The cross-entropy theory is used to optimise the gains of our controllers. The optimization process was made using the ROS-Gazebo 3D simulation with purposeful extensions developed for our experiments. Visual servoing is achieved through an image processing front-end that uses the Camshift algorithm to detect and track objects in the scene. Experimental flight trials using a small quadrotor were performed to validate the parameters estimated from simulation. The integration of crossentropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights.

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.

Arquitectura cognitiva híbrida para la navegación autónoma de UAVs mediante mapas topológicos visuales

El objetivo fundamental de la presente tesis doctoral es el diseño de una arquitectura cognitiva, que pueda ser empleada para la navegación autónoma de vehículos aéreos no tripulados conocidos como UAV (Unmanned Aerial Vehicle). Dicha arquitectura cognitiva se apoya en la definición de una librería de comportamientos, que aportarán la inteligencia necesaria al UAV para alcanzar los objetivos establecidos, en base a la información sensorial recopilada del entorno de operación. La navegación autónoma del UAV se apoyará en la utilización de un mapa topológico visual, consistente en la definición de un grafo que engloba mediante nodos los diferentes landmarks ubicados en el entorno, y que le servirán al UAV de guía para alcanzar su objetivo. Los arcos establecidos entre los nodos del mapa topológico, le proporcionarán de la información necesaria para establecer el rumbo más adecuado para alcanzar el siguiente landmark a visitar, siguiendo siempre una secuencia lógica de navegación, basada en la distancia entre un determinado landmark con respecto al objetivo final ó landmark destino. La arquitectura define un mecanismo híbrido de control, el cual puede conmutar entre dos diferentes modos de navegación. El primero es el denominado como Search Mode, el cual se activará cuando el UAV se encuentre en un estado desconocido dentro del entorno, para lo cual hará uso de cálculos basado en la entropía para la búsqueda de posibles landmarks. Se empleará como estrategia novedosa la idea de que la entropía de una imagen tiene una correlación directa con respecto a la probabilidad de que dicha imagen contenga uno ó varios landmarks. De esta forma, la estrategia para la búsqueda de nuevos landmarks en el entorno, se basará en un proceso continuo de maximización de la entropía. Si por el contrario el UAV identifica la existencia de un posible landmark entre los definidos en su mapa topológico, se considerará que está sobre un estado conocido, por lo que se conmutará al segundo modo de navegación denominado como Homing Mode, el cual se encargará de calcular señales de control para la aproximación del UAV al landmark localizado. Éste último modo implementa un control dual basado en dos tipos de controladores (FeedForward/FeedBack) que mediante su combinación, aportarán al UAV señales de control cada vez más óptimas, además de llevar a cabo un entrenamiento continuo y en tiempo real. Para cumplir con los requisitos de ejecución y aprendizaje en tiempo real de la arquitectura, se han tomado como principales referencias dos paradigmas empleados en diferentes estudios dentro del área de la robótica, como son el paradigma de robots de desarrollo (developmental robots) basado en un aprendizaje del robot en tiempo real y de forma adaptativa con su entorno, así como del paradigma de modelos internos (internal models) basado en los resultados obtenidos a partir de estudios neurocientíficos del cerebelo humano; dicho modelo interno sirve de base para la construcción del control dual de la arquitectura. Se presentarán los detalles de diseño e implementación de los diferentes módulos que componen la arquitectura cognitiva híbrida, y posteriormente, los diferentes resultados obtenidos a partir de las pruebas experimentales ejecutadas, empleando como UAV la plataforma robótica aérea de AR.Drone. Como resultado final se ha obtenido una validación completa de la arquitectura cognitiva híbrida objetivo de la tesis, cumplimento con la totalidad de requisitos especificados y garantizando su viabilidad como aplicación operativa en el mundo real. Finalmente, se muestran las distintas conclusiones a las cuales se ha llegado a partir de los resultados experimentales, y se presentan las diferentes líneas de investigación futuras que podrán ser ejecutadas.

New generation of human machine interfaces for controlling UAV through depth based gesture recognition

New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

Sistema de soporte al desarrollo de un planificador de misiones en un vehículo aéreo no tripulado

En esta memoria se describe el trabajo de construcción de una arquitectura software diseñada para facilitar el desarrollo un planificador de misión de un vehículo aéreo no tripulado (UAV), con el fin de que éste alcance los objetivos marcados en la competición internacional de robótica IARC (séptima edición). A lo largo de la memoria, se describe en primer lugar, una revisión de técnicas de robótica inteligente aplicadas a la construcción de vehículos aéreos no tripulados, en el que se ven los diferentes paradigmas de programación de la robótica inteligente y la clasificación de dichos robots aéreos, dependiendo de su autonomía. Este descripción finaliza con la presentación del problema correspondiente a la competición IARC. A continuación se describe el diseño realizado para soporte al desarrollo de un planificador de misiones de UAVs, con simulación de comportamiento de vehículos robóticos y visualización 3D con movimiento. Finalmente, se muestran las pruebas que se han realizado para validar la construcción de dicha arquitectura software. ---ABSTRACT---In this report it is presented the construction of a software architecture, designed to facilitate the development of a mission planner for an unmanned aerial vehicle (UAV), so that it reaches the goals set in the International Aerial Robotics Competition - IARC (seventh edition). Throughout this report, it is described first, a review of intelligent robotics techniques applied to the construction of unmanned aerial vehicles, where different paradigms of intelligent robotics are seen, along with a classification of such aerial robots, depending on their autonomy. Description ends with the presentation of the problem corresponding to the IARC competition. Following, it is described the design made to satisfy the support to the development of a mission planner for UAV´s, with a simulation of the robotics vehicles’ behaviours and a 3D display with motion. Finally, we will deal with the tests that have been conducted to validate the construction of the software architecture.

Control reactivo de vehículo aéreo no tripulado para la competición internacional IARC

El trabajo está centrado en la construcción de una simulación y en el desarrollo de un control reactivo para un vehículo aéreo no tripulado con fin de participar en la séptima edición de la competición internacional IARC. Para cumplir los objetivos de la competición se van a estudiar técnicas existentes de inteligencia artificial aplicadas al control de vehículos aéreos no tripulados, así como las técnicas para la elaboración de un modelo de simulación realista sobre el que realizar las distintas pruebas. Por último, se explica el trabajo realizado para crear un controlador reactivo que satisface las reglas de la competición y permite al vehículo aéreo no tripulado operar de forma autónoma en el ambiente de la simulación. Para validar el comportamiento, se realizan casos de prueba y un estudio de los resultados.---ABSTRACT---This report is focused on the construction of a simulation and the development of a reactive control for an unmanned aerial vehicle in order to participate in the seventh edition of the international competition IARC. Artificial intelligence techniques applied to the control of unmanned aerial vehicles are going to be studied to meet the objectives of the competition, as well as techniques for developing a realistic simulation model on which to perform the different tests. Finally, the last part of the report explains the work accomplished to create a reactive controller that meets the rules of the competition and allows the unmanned aerial vehicle to operate autonomously in the simulation environment. Test cases and a study of the results is performed to validate the behavior.