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.

Optimal Piecewise Linear Function Approximation for GPU-based Applications

Many computer vision and human-computer interaction applications developed in recent years need evaluating complex and continuous mathematical functions as an essential step toward proper operation. However, rigorous evaluation of this kind of functions often implies a very high computational cost, unacceptable in real-time applications. To alleviate this problem, functions are commonly approximated by simpler piecewise-polynomial representations. Following this idea, we propose a novel, efficient, and practical technique to evaluate complex and continuous functions using a nearly optimal design of two types of piecewise linear approximations in the case of a large budget of evaluation subintervals. To this end, we develop a thorough error analysis that yields asymptotically tight bounds to accurately quantify the approximation performance of both representations. It provides an improvement upon previous error estimates and allows the user to control the trade-off between the approximation error and the number of evaluation subintervals. To guarantee real-time operation, the method is suitable for, but not limited to, an efficient implementation in modern Graphics Processing Units (GPUs), where it outperforms previous alternative approaches by exploiting the fixed-function interpolation routines present in their texture units. The proposed technique is a perfect match for any application requiring the evaluation of continuous functions, we have measured in detail its quality and efficiency on several functions, and, in particular, the Gaussian function because it is extensively used in many areas of computer vision and cybernetics, and it is expensive to evaluate.

Sistema colaborativo de detección y seguimiento de anomalías mediante visión por computador

En este proyecto se realiza el diseño e implementación de un sistema que detecta anomalías en las entradas de entornos controlados. Para ello, se hace uso de las últimas técnicas en visión por computador y se avisa visual y auditivamente, mediante un sistema hardware que recibe señales del ordenador al que está conectado. Se marca y fotografía, a una o varias personas, que cometen una infracción en las entradas de un establecimiento, vigilado con sistemas de vídeo. Las imágenes se almacenan en las carpetas correspondientes. El sistema diseñado es colaborativo, por lo tanto, las cámaras que intervienen, se comunican entre ellas a través de estructuras de datos con el objetivo de intercambiar información. Además, se utiliza conexión inalámbrica desde un dispositivo móvil para obtener una visión global del entorno desde cualquier lugar del mundo. La aplicación se desarrolla en el entorno MATLAB, que permite un tratamiento de la señal de imagen apropiado para el presente proyecto. Asimismo, se proporciona al usuario una interfaz gráfica con la que interactuar de manera sencilla, evitando así, el cambio de parámetros en la estructura interna del programa cuando se quiere variar el entorno o el tipo de adquisición de datos. El lenguaje que se escoge facilita la ejecución en distintos sistemas operativos, incluyendo Windows o iOS y, de esta manera, se proporciona flexibilidad. ABSTRACT. This project studies the design and implementation of a system that detects any anomalies on the entrances to controlled environments. To this end, it is necessary the use of last techniques in computer vision in order to notify visually and aurally, by a hardware system which receives signs from the computer it is connected to. One or more people that commit an infringement while entering into a secured environment, with video systems, are marked and photographed and those images are stored in their belonging file folder. This is a collaborative design system, therefore, every involved camera communicates among themselves through data structures with the purpose of exchanging information. Furthermore, to obtain a global environment vision from any place in the world it uses a mobile wireless connection. The application is developed in MATLAB environment because it allows an appropriate treatment of the image signal for this project. In addition, the user is given a graphical interface to easily interact, avoiding with this, changing any parameters on the program’s intern structure, when it requires modifying the environment or the data type acquisition. The chosen language eases its execution in different operating systems, including Windows or iOS, providing flexibility.