Robots for Exploration, Digital Preservation and Visualization of Archeological Sites

Monitoring and conservation of archaeological sites are important activities necessary to prevent damage or to perform restoration on cultural heritage. Standard techniques, like mapping and digitizing, are typically used to document the status of such sites. While these task are normally accomplished manually by humans, this is not possible when dealing with hard-to-access areas. For example, due to the possibility of structural collapses, underground tunnels like catacombs are considered highly unstable environments. Moreover, they are full of radioactive gas radon that limits the presence of people only for few minutes. The progress recently made in the artificial intelligence and robotics field opened new possibilities for mobile robots to be used in locations where humans are not allowed to enter. The ROVINA project aims at developing autonomous mobile robots to make faster, cheaper and safer the monitoring of archaeological sites. ROVINA will be evaluated on the catacombs of Priscilla (in Rome) and S. Gennaro (in Naples)

Underwater Automated Vehicle

Design and fabricate an Automated Underwater Vehicle (AUV) which consisted of four vertical thurster, two horizontal thruster and gyroscope together with accelerometer for self – leveling to counter unbalance orientation while carrying loads. Also consisted with pressure sensor to control depth positioning without deviation, and underwater GPS based navigation system in the restricted electromagnetic signal medium. The scope of study for this project involved combination of mechanical and electrical knowledge, where the mechanical chassis was designed using Autodesk Inventor 2014 software before fabrication process to ensure the design has required quality. Then, the fabricated design were equipped with electronics part, consisting of programmed microcontroller, motor drivers, and other electronic sensors for feedback to achieve the desired output

Real Time Stereo Cameras System Calibration Tool and Attitude and Pose Computation with Low Cost Cameras

The Engineering in autonomous systems has many strands. The area in which this work falls, the artificial vision, has become one of great interest in multiple contexts and focuses on robotics. This work seeks to address and overcome some real difficulties encountered when developing technologies with artificial vision systems which are, the calibration process and pose computation of robots in real-time. Initially, it aims to perform real-time camera intrinsic (3.2.1) and extrinsic (3.3) stereo camera systems calibration needed to the main goal of this work, the real-time pose (position and orientation) computation of an active coloured target with stereo vision systems. Designed to be intuitive, easy-to-use and able to run under real-time applications, this work was developed for use either with low-cost and easy-to-acquire or more complex and high resolution stereo vision systems in order to compute all the parameters inherent to this same system such as the intrinsic values of each one of the cameras and the extrinsic matrices computation between both cameras. More oriented towards the underwater environments, which are very dynamic and computationally more complex due to its particularities such as light reflections. The available calibration information, whether generated by this tool or loaded configurations from other tools allows, in a simplistic way, to proceed to the calibration of an environment colorspace and the detection parameters of a specific target with active visual markers (4.1.1), useful within unstructured environments. With a calibrated system and environment, it is possible to detect and compute, in real time, the pose of a target of interest. The combination of position and orientation or attitude is referred as the pose of an object. For performance analysis and quality of the information obtained, this tools are compared with others already existent.A engenharia de sistemas autónomos actua em diversas vertentes. Uma delas, a visão artificial, em que este trabalho assenta, tornou-se uma das de maior interesse em múltiplos contextos e focos na robótica. Assim, este trabalho procura abordar e superar algumas dificuldades encontradas aquando do desenvolvimento de tecnologias baseadas na visão artificial. Inicialmente, propõe-se a fornecer ferramentas para realizar as calibrações necessárias de intrínsecos (3.2.1) e extrínsecos (3.3) de sistemas de visão stereo em tempo real para atingir o objectivo principal, uma ferramenta de cálculo da posição e orientação de um alvo activo e colorido através de sistemas de visão stereo. Desenhadas para serem intuitivas, fáceis de utilizar e capazes de operar em tempo real, estas ferramentas foram desenvolvidas tendo em vista a sua integração quer com camaras de baixo custo e aquisição fácil como com camaras mais complexas e de maior resolução. Propõem-se a realizar a calibração dos parâmetros inerentes ao sistema de visão stereo como os intrínsecos de cada uma das camaras e as matrizes de extrínsecos que relacionam ambas as camaras. Este trabalho foi orientado para utilização em meio subaquático onde se presenciam ambientes com elevada dinâmica visual e maior complexidade computacional devido `a suas particularidades como reflexões de luz e má visibilidade. Com a informação de calibração disponível, quer gerada pelas ferramentas fornecidas, quer obtida a partir de outras, pode ser carregada para proceder a uma calibração simplista do espaço de cor e dos parâmetros de deteção de um alvo específico com marcadores ativos coloridos (4.1.1). Estes marcadores são ´uteis em ambientes não estruturados. Para análise da performance e qualidade da informação obtida, as ferramentas de calibração e cálculo de pose (posição e orientação), serão comparadas com outras já existentes

2D position system for a mobile robot in unstructured environments

Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability