A Ground-Truth Video Dataset for the Development and Evaluation of Vision-based Sense-and-Avoid systems

The importance of vision-based systems for Sense-and-Avoid is increasing nowadays as remotely piloted and autonomous UAVs become part of the non-segregated airspace. The development and evaluation of these systems demand flight scenario images which are expensive and risky to obtain. Currently Augmented Reality techniques allow the compositing of real flight scenario images with 3D aircraft models to produce useful realistic images for system development and benchmarking purposes at a much lower cost and risk. With the techniques presented in this paper, 3D aircraft models are positioned firstly in a simulated 3D scene with controlled illumination and rendering parameters. Realistic simulated images are then obtained using an image processing algorithm which fuses the images obtained from the 3D scene with images from real UAV flights taking into account on board camera vibrations. Since the intruder and camera poses are user-defined, ground truth data is available. These ground truth annotations allow to develop and quantitatively evaluate aircraft detection and tracking algorithms. This paper presents the software developed to create a public dataset of 24 videos together with their annotations and some tracking application results

Computer Vision Based General Object Following for GPS-denied Multirotor Unmanned Vehicles

The motivation of this research is to show that visual based object tracking and following is reliable using a cheap GPS-denied multirotor platform such as the AR Drone 2.0. Our architecture allows the user to specify an object in the image that the robot has to follow from an approximate constant distance. At the current stage of our development, in the event of image tracking loss the system starts to hover and waits for the image tracking recovery or second detection, which requires the usage of odometry measurements for self stabilization. During the following task, our software utilizes the forward-facing camera images and part of the IMU data to calculate the references for the four on-board low-level control loops. To obtain a stronger wind disturbance rejection and an improved navigation performance, a yaw heading reference based on the IMU data is internally kept and updated by our control algorithm. We validate the architecture using an AR Drone 2.0 and the OpenTLD tracker in outdoor suburban areas. The experimental tests have shown robustness against wind perturbations, target occlusion and illumination changes, and the system's capability to track a great variety of objects present on suburban areas, for instance: walking or running people, windows, AC machines, static and moving cars and plants

Toward Visual Autonomous Ship Board Landing of a VTOL UAV

In this paper we tackle the problem of landing a helicopter autonomously on a ship deck, using as the main sensor, an on-board colour camera. To create a test-bed, we first adequately simulate the movement of a ship landing platform on the Sea, for different Sea States, for different ships, randomly and realistically enough. We use a commercial parallel robot to get this movement. Once we had this, we developed an accurate and robust computer vision system to measure the pose of the helipad with respect to the on-board camera. To deal with the noise and the possible fails of the computer vision, a state estimator was created. With all of this, we are now able to develop and test a controller that closes the loop and finish the autonomous landing task

AR drone identification and navigation control at CVG-UPM

This article presents the proposal of the Computer Vision Group to the first phase of the international competition “Concurso de Ingeniería de Control 2012, Control Aut ́onomo del seguimiento de trayectorias de un vehículo cuatrirrotor”. This phase consists mainly of two parts: identifying a model and designing a trajectory controller for the AR Drone quadrotor. For the identification task, two models are proposed: a simplified model that captures only the main dynamics of the quadrotor, and a second model based on the physical laws underlying the AR Drone behavior. The trajectory controller design is based on the simplified model, whereas the physical model is used to tune the controller to attain a certain level of robust stability to model uncertainties. The controller design is simplified by the hypothesis that accurate positions sensors will be available to implement a feedback controller

CUESTIONARIO SOBRE NECESIDADES FORMATIVAS DEL PROFESORADO DE NUEVO INGRESO ANTE EL RETO DE LA PANDEMIA (ITAPÚA, PARAGUAY)

En esta investigación se expone el proceso de construcción y validación de un instrumento efectivo y confiable para conocer la formación y necesidades que tiene el profesorado de nuevo ingreso, ante los nuevos cambios didácticos y retos tecnológicos en el Campus Itapúa de la Universidad Católica “Nuestra Señora de la Asunción” (UC). El análisis de los datos estadísticos verificó la validez y la fiabilidad del cuestionario/escala. La fiabilidad del cuestiona quedó demostrada al obtener un alfa de Cronbach para 17 ítems de ,900. La validez de constructo con el análisis factorial confirmatorio se ha realizado mediante el modelo de ecuaciones estructurales (“Structural Equation Modeling”, SEM). Se trata de una técnica que combina tanto la regresión múltiple como el análisis factorial mediante las fases de especificación, identificación, estimación de parámetros, evaluación del ajuste, re especificación del modelo e interpretación de resultados. Los principales coeficientes e índices de bondad de ajuste indican un ajuste del modelo óptimo (RMSEA = ,076; RMR = ,048; CFI = ,901; TLI = ,902). Se concluye que el cuestionario integra los componentes la formación y necesidades que tiene el profesorado de nuevo ingreso, ante los nuevos cambios didácticos y retos tecnológicos a causa de la pandemia y se demuestra su representatividad con las dimensiones del cuestionario

The Andalusian Tourism Sector during the Economic Crisis and its Impact on Regional Development

Son frecuentes las referencias a los efectos benéficos del sector turístico para el Desarrollo Regional; incluso es habitual esgrimir precisiones al respecto, prácticamente sin medir el hecho. En este trabajo pretendemos, basándonos en la modelización mediante Matrices de Contabilidad Social (MCS), conocer cómo se ha mostrado una región tan especializada en turismo como Andalucía, especialmente en el momento más profundo de la crisis económica. Destacamos por un lado el interés de aplicar las MCS (en los años 2010 y 2014), que nos permiten calificar el sector turístico andaluz como un sector productivo clave para la economía regional. Además, estableceremos relaciones con la coyuntura última del turismo regional, para considerar si este comportamiento es sostenible en términos territoriales y económicos, o simplemente es episódico. Se analizará la variable empleo más prolijamente, dado que es el problema por excelencia en regiones semiperiféricas de desarrollo intermedio, y además con una anomalía muy negativa en Andalucía. Nos interesa destacar el papel del turismo en la economía andaluza y sus efectos sobre el desarrollo.Los resultados pondrán de manifiesto que las debilidades estructurales del sector han quedado de manifiesto a la salida de la crisis: concentración espacial, temporalidad del empleo, insuficiencia tecnológica y un gasto turístico alejado del pretendido turismo de calidad. Habitualmente se recurre al turismo como actividad estratégica en la creación de empleo, si bien nuestros resultados en este sentido no son nada alentadores. Las primeras certezas nos orientan en una aportación del sector sobre el Desarrollo Regional, pero más por defecto de lo destruido en la crisis, que por propio efecto motor.It is not common practice to assess tourism’s effects on regional development, although its benefits for host economies are widely known. This paper attempts to discern such activity’s role in a geographic setting by applying structural analysis techniquesbased on social accounting matrices (SAMs). This methodological approach is applied to the case of Andalusia during the period 2010-2014, encompassing both the financial crisis period and the apparent resurgence. The research aims to reflect on the andalusian economy from the perspective of tourism and know its impacts on the regional territory. The proposed methodology is applied to a region where tourism became more prominent during the financial crisis. The results indicate that tourism’s significancein the host economy is due its own particular behaviour and also to the performance of other economic sectors during the study period. Tourism has shown considerable carry-over capacity in the territory, although challenges have arisen in employment, demand and technological density aspects. All of them should be addressed so that tourism can provide a sustainable support for regional development. Tourism sector’s appeared as a strategic sector, partly due to its specific performance, though also to the other sectors’ performance, either declining industries such as construction or with lighter presence, as in the case of industrial activities. Tourism has also shown itself to be a pro-cyclical sector, with landmarks. Yet the tourism sector has shown provenresilience and a considerable ability to foster economic development in the territory

A Vision-based Quadrotor Swarm for the participation in the 2013 International Micro Air Vehicle Competition

This paper presents a completely autonomous solution to participate in the 2013 International Micro Air Vehicle Indoor Flight Competition (IMAV2013). Our proposal is a modular multi-robot swarm architecture, based on the Robot Operating System (ROS) software framework, where the only information shared among swarm agents is each robot's position. Each swarm agent consists of an AR Drone 2.0 quadrotor connected to a laptop which runs the software architecture. In order to present a completely visual-based solution the localization problem is simplified by the usage of ArUco visual markers. These visual markers are used to sense and map obstacles and to improve the pose estimation based on the IMU and optical data flow by means of an Extended Kalman Filter localization and mapping method. The presented solution and the performance of the CVG UPM team were awarded with the First Prize in the Indoors Autonomy Challenge of the IMAV2013 competition

A System for the Design and Development of Vision-based Multi-robot Quadrotor Swarms

This paper presents a cost-effective framework for the prototyping of vision-based quadrotor multi-robot systems, which core characteristics are: modularity, compatibility with different platforms and being flight-proven. The framework is fully operative, which is shown in the paper through simulations and real flight tests of up to 5 drones, and was demonstrated with the participation in an international micro-aerial vehicles competition3 where it was awarded with the First Prize in the Indoors Autonomy Challenge. The motivation of this framework is to allow the developers to focus on their own research by decoupling the development of dependent modules, leading to a more cost-effective progress in the project. The basic instance of the framework that we propose, which is flight-proven with the cost-efficient and reliable platform Parrot AR Drone 2.0 and is open-source, includes several modules that can be reused and modified, such as: a basic sequential mission planner, a basic 2D trajectory planner, an odometry state estimator, localization and mapping modules which obtain absolute position measurements using visual markers, a trajectory controller and a visualization module

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

A System for the Design and Development of Vision-based Multi-robot Quadrotor Swarms

This paper presents a cost-effective framework for the prototyping of vision-based quadrotor multi-robot systems, which core characteristics are: modularity, compatibility with different platforms and being flight-proven. The framework is fully operative, which is shown in the paper through simulations and real flight tests of up to 5 drones, and was demonstrated with the participation in an international micro-aerial vehicles competition3 where it was awarded with the First Prize in the Indoors Autonomy Challenge. The motivation of this framework is to allow the developers to focus on their own research by decoupling the development of dependent modules, leading to a more cost-effective progress in the project. The basic instance of the framework that we propose, which is flight-proven with the cost-efficient and reliable platform Parrot AR Drone 2.0 and is open-source, includes several modules that can be reused and modified, such as: a basic sequential mission planner, a basic 2D trajectory planner, an odometry state estimator, localization and mapping modules which obtain absolute position measurements using visual markers, a trajectory controller and a visualization module