Robust vision based slope estimation and rocks detection for autonomous space landers

As future robotic surface exploration missions to other planets, moons and asteroids become more ambitious in their science goals, there is a rapidly growing need to significantly enhance the capabilities of entry, descent and landing technology such that landings can be carried out with pin-point accuracy at previously inaccessible sites of high scientific value. As a consequence of the extreme uncertainty in touch-down locations of current missions and the absence of any effective hazard detection and avoidance capabilities, mission designers must exercise extreme caution when selecting candidate landing sites. The entire landing uncertainty footprint must be placed completely within a region of relatively flat and hazard free terrain in order to minimise the risk of mission ending damage to the spacecraft at touchdown. Consequently, vast numbers of scientifically rich landing sites must be rejected in favour of safer alternatives that may not offer the same level of scientific opportunity. The majority of truly scientifically interesting locations on planetary surfaces are rarely found in such hazard free and easily accessible locations, and so goals have been set for a number of advanced capabilities of future entry, descent and landing technology. Key amongst these is the ability to reliably detect and safely avoid all mission critical surface hazards in the area surrounding a pre-selected landing location. This thesis investigates techniques for the use of a single camera system as the primary sensor in the preliminary development of a hazard detection system that is capable of supporting pin-point landing operations for next generation robotic planetary landing craft. The requirements for such a system have been stated as the ability to detect slopes greater than 5 degrees and surface objects greater than 30cm in diameter. The primary contribution in this thesis, aimed at achieving these goals, is the development of a feature-based,self-initialising, fully adaptive structure from motion (SFM) algorithm based on a robust square-root unscented Kalman filtering framework and the fusion of the resulting SFM scene structure estimates with a sophisticated shape from shading (SFS) algorithm that has the potential to produce very dense and highly accurate digital elevation models (DEMs) that possess sufficient resolution to achieve the sensing accuracy required by next generation landers. Such a system is capable of adapting to potential changes in the external noise environment that may result from intermittent and varying rocket motor thrust and/or sudden turbulence during descent, which may translate to variations in the vibrations experienced by the platform and introduce varying levels of motion blur that will affect the accuracy of image feature tracking algorithms. Accurate scene structure estimates have been obtained using this system from both real and synthetic descent imagery, allowing for the production of accurate DEMs. While some further work would be required in order to produce DEMs that possess the resolution and accuracy needed to determine slopes and the presence of small objects such as rocks at the levels of accuracy required, this thesis presents a very strong foundation upon which to build and goes a long way towards developing a highly robust and accurate solution

Mobile robot vavigation using a vision based approach

PhD ThesisThis study addresses the issue of vision based mobile robot navigation in a partially cluttered indoor environment using a mapless navigation strategy. The work focuses on two key problems, namely vision based obstacle avoidance and vision based reactive navigation strategy. The estimation of optical flow plays a key role in vision based obstacle avoidance problems, however the current view is that this technique is too sensitive to noise and distortion under real conditions. Accordingly, practical applications in real time robotics remain scarce. This dissertation presents a novel methodology for vision based obstacle avoidance, using a hybrid architecture. This integrates an appearance-based obstacle detection method into an optical flow architecture based upon a behavioural control strategy that includes a new arbitration module. This enhances the overall performance of conventional optical flow based navigation systems, enabling a robot to successfully move around without experiencing collisions. Behaviour based approaches have become the dominant methodologies for designing control strategies for robot navigation. Two different behaviour based navigation architectures have been proposed for the second problem, using monocular vision as the primary sensor and equipped with a 2-D range finder. Both utilize an accelerated version of the Scale Invariant Feature Transform (SIFT) algorithm. The first architecture employs a qualitative-based control algorithm to steer the robot towards a goal whilst avoiding obstacles, whereas the second employs an intelligent control framework. This allows the components of soft computing to be integrated into the proposed SIFT-based navigation architecture, conserving the same set of behaviours and system structure of the previously defined architecture. The intelligent framework incorporates a novel distance estimation technique using the scale parameters obtained from the SIFT algorithm. The technique employs scale parameters and a corresponding zooming factor as inputs to train a neural network which results in the determination of physical distance. Furthermore a fuzzy controller is designed and integrated into this framework so as to estimate linear velocity, and a neural network based solution is adopted to estimate the steering direction of the robot. As a result, this intelligent iv approach allows the robot to successfully complete its task in a smooth and robust manner without experiencing collision. MS Robotics Studio software was used to simulate the systems, and a modified Pioneer 3-DX mobile robot was used for real-time implementation. Several realistic scenarios were developed and comprehensive experiments conducted to evaluate the performance of the proposed navigation systems. KEY WORDS: Mobile robot navigation using vision, Mapless navigation, Mobile robot architecture, Distance estimation, Vision for obstacle avoidance, Scale Invariant Feature Transforms, Intelligent framework

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest

リフティング構造を利用した非分離型ウェーブレット変換のノイズ低減に関する研究

国立大学法人長岡技術科学大

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

Digital Watermarking for Verification of Perception-based Integrity of Audio Data

In certain application fields digital audio recordings contain sensitive content. Examples are historical archival material in public archives that preserve our cultural heritage, or digital evidence in the context of law enforcement and civil proceedings. Because of the powerful capabilities of modern editing tools for multimedia such material is vulnerable to doctoring of the content and forgery of its origin with malicious intent. Also inadvertent data modification and mistaken origin can be caused by human error. Hence, the credibility and provenience in terms of an unadulterated and genuine state of such audio content and the confidence about its origin are critical factors. To address this issue, this PhD thesis proposes a mechanism for verifying the integrity and authenticity of digital sound recordings. It is designed and implemented to be insensitive to common post-processing operations of the audio data that influence the subjective acoustic perception only marginally (if at all). Examples of such operations include lossy compression that maintains a high sound quality of the audio media, or lossless format conversions. It is the objective to avoid de facto false alarms that would be expectedly observable in standard crypto-based authentication protocols in the presence of these legitimate post-processing. For achieving this, a feasible combination of the techniques of digital watermarking and audio-specific hashing is investigated. At first, a suitable secret-key dependent audio hashing algorithm is developed. It incorporates and enhances so-called audio fingerprinting technology from the state of the art in contentbased audio identification. The presented algorithm (denoted as ”rMAC” message authentication code) allows ”perception-based” verification of integrity. This means classifying integrity breaches as such not before they become audible. As another objective, this rMAC is embedded and stored silently inside the audio media by means of audio watermarking technology. This approach allows maintaining the authentication code across the above-mentioned admissible post-processing operations and making it available for integrity verification at a later date. For this, an existent secret-key ependent audio watermarking algorithm is used and enhanced in this thesis work. To some extent, the dependency of the rMAC and of the watermarking processing from a secret key also allows authenticating the origin of a protected audio. To elaborate on this security aspect, this work also estimates the brute-force efforts of an adversary attacking this combined rMAC-watermarking approach. The experimental results show that the proposed method provides a good distinction and classification performance of authentic versus doctored audio content. It also allows the temporal localization of audible data modification within a protected audio file. The experimental evaluation finally provides recommendations about technical configuration settings of the combined watermarking-hashing approach. Beyond the main topic of perception-based data integrity and data authenticity for audio, this PhD work provides new general findings in the fields of audio fingerprinting and digital watermarking. The main contributions of this PhD were published and presented mainly at conferences about multimedia security. These publications were cited by a number of other authors and hence had some impact on their works

Estudios funcionales mediante resonancia magnética en pequeños animales

This thesis is framed within the field of preclinical biomedical imaging, and specifically devoted to the study of functional magnetic resonance imaging (fMRI) technique in small animals. The experimental and technological complexity of this modality has greatly limited its use, and therefore it is not a routine imaging modality. However, it provides valuable information both at the physiological level, to study the mechanisms of normal brain during neuronal activity, and at the pathological level, to study drugs intended for different brain dysfunctions. In this work we have studied techniques and methods that intend to alleviate these difficulties and facilitate their use by the scientific community. The work includes contributions at several stages: the experimental setup, the data acquisition and reconstruction, and the quantitative image analysis. The first section addresses the problem of using anesthesia during the experiment. In order to perform functional measurements, it is necessary to establish a protocol to induce anesthetic sedation of the animal rather than a deep anesthetic state. Moreover, the use of non-toxic drugs with fast induction and recovery is desirable. In this section of the thesis we conducted fMRI experiments in rats sedated with sevoflurane, and since this agent had not been previously reported for fMRI, it was necessary to conduct strategies in order to determine the optimum dose-response and stimulation frequency. Furthermore, the signal obtained in the cerebral cortex was compared with a more traditional protocol sedation, subdermal medetomidine. The signal obtained was similar to that obtained under medetomidine, but the animal preparation time increased considerably, which constitutes a serious practical drawback for the use of sevoflurane. The second section is devoted to the study of a compressed sensing framework that allows a substantial reduction on the acquisition time without degrading image quality. The acquisition of a much reduced amount of data, thus at high rates of acceleration that violate the Nyquist-Shannon criterion, is possible by means of a wise exploitation of the temporal information redundancy and by the use of nonlinear iterative reconstruction algorithms. In this study we evaluated the performance of three compressed-sensing reconstruction algorithms that exploit temporal redundancy to recover the BOLD contrast and which have proved successful in other applications or imaging modalities such as: X-ray tomography, dynamic cardiac MRI, and resting state MRI studies. The comparison was performed in two signal-to-noise ratio scenarios and the conclusion drawn is that the algorithm which uses an a priori image (PICCS) yields the best reconstruction. The third section deals with the post-processing and image analysis. There are several open-source tools available to this purpose, but they were originally designed for human studies. Their adaptation to rodent images requires the use of additional tools or some image transformation processing that involve programming skills. Moreover, to obtain quantitative values, the user would need to use additional extensions or external software. In this work we have studied the existing tools and proposed and developed a new software, fMRat, which automatically performs a full multi-subject analysis, from the initial format conversion to the extraction of numerical values from the regions interest chosen by the user. The tool was programmed in Matlab as an extension of the existing SPM package, and was validated with 460 real rat studies. The code has been published as "open-software" in Github website and is accessible to the neuroscience community.Esta tesis se enmarca dentro del ámbito de la imagen biomédica preclínica, y específicamente trata sobre la técnica de imagen de resonancia magnética funcional (fMRI) en pequeños animales. La complejidad de dicha técnica tanto a nivel experimental como tecnológico ha limitado considerablemente su ámbito de uso, y por ello no es una modalidad de imagen que se realice de manera habitual. Sin embargo ofrece información muy valiosa tanto a nivel fisiológico, para el estudio de los mecanismos del cerebro normal durante la actividad neuronal, como a nivel patológico, para la búsqueda y estudio de fármacos aplicables a diferentes disfunciones cerebrales. En esta tesis se han estudiado técnicas y métodos para intentar aliviar estas dificultades y facilitar su utilización por parte de la comunidad científica. El trabajo incluye aportaciones en los ámbitos de la configuración del experimento, de la adquisición de los datos y su reconstrucción, y por último del análisis cuantitativo final de las imágenes. En el primer capítulo se trata el problema del uso de anestesia durante el experimento. Para obtener medidas funcionales es necesario establecer un protocolo anestésico que facilite la sedación del animal pero sin llegar a un estado anestésico profundo. Por otra parte, es deseable que sea de rápida inducción y recuperación, y que no sea tóxico para que pueda usarse en estudios longitudinales. En esta parte de la tesis se realizaron experimentos de fMRI en rata sedada con sevofluorano, para lo cual fue necesario realizar un estudio dosis-respuesta y un barrido de frecuencias de estimulación. Además, la señal obtenida en la corteza cerebral se comparó con la de otro protocolo de sedación más tradicional, con medetomidina subdérmica. La señal obtenida fue de intensidad similar a la obtenida con medetomidina, pero el tiempo de preparación del animal se incrementó considerablemente, lo cual constituye un grave inconveniente práctico para el uso de este anestésico. El segundo capítulo está dedicado al estudio de un entorno de adquisición comprimida o “compressed sensing” que permita reducir sustancialmente el tiempo de adquisición sin degradar la calidad de la imagen, gracias a la adquisición de una cantidad mucho menor de datos. En este trabajo se muestra que sería posible acelerar la adquisición a altas tasas que incumplen el criterio de Nyquist-Shannon siempre y cuando se explote la redundancia de información temporal y al mismo tiempo se empleen algoritmos de reconstrucción de imagen iterativos no lineales. En concreto se compara la eficacia de tres algoritmos de reconstrucción que explotan la redundancia temporal para recuperar el contraste BOLD y que han arrojado buenos resultados en otras aplicaciones o modalidades de imagen: tomografía por rayos X, estudios dinámicos de corazón por resonancia magnética, y resonancia funcional en reposo o “resting state”. La comparativa se realizó en dos escenarios de relación señal a ruido y se concluye que el algoritmo que utiliza una imagen a priori (PICCS) es el que mejores resultados obtiene en la reconstrucción. El tercer capítulo aborda el postprocesado y análisis de las imágenes. Existen varias herramientas gratuitas y de código abierto para este fin, pero fueron diseñadas para imagen de cerebro humano, y su adaptación a imágenes de roedores requiere el uso de herramientas adicionales o la realización de transformaciones en la imagen que implican conocimientos de programación. Además, para obtener valores cuantitativos es imprescindible el uso de extensiones o herramientas adicionales. En este trabajo se han estudiado las herramientas existentes y se ha propuesto y desarrollado un nuevo software, fMRat, que realiza el análisis completo de varios sujetos de manera automática, desde el cambio de formato de las imágenes hasta la obtención de valores numéricos de las regiones de interés elegidas por el usuario. La herramienta está programada en Matlab como una extensión de un paquete SPM ya existente, y fue validada con 460 estudios reales de ratas. El código está publicado como “opensoftware” en el sitio web de Github y es accesible a cualquier neurocientífico que desee utilizarlo.Programa Oficial de Doctorado en Multimedia y ComunicacionesPresidente: Pedro Ramos Cabrer.- Secretario: Juan Miguel Parra Robles.- Vocal: María Jesús Ledesma Carbay

Advances in Image Processing, Analysis and Recognition Technology

For many decades, researchers have been trying to make computers’ analysis of images as effective as the system of human vision is. For this purpose, many algorithms and systems have previously been created. The whole process covers various stages, including image processing, representation and recognition. The results of this work can be applied to many computer-assisted areas of everyday life. They improve particular activities and provide handy tools, which are sometimes only for entertainment, but quite often, they significantly increase our safety. In fact, the practical implementation of image processing algorithms is particularly wide. Moreover, the rapid growth of computational complexity and computer efficiency has allowed for the development of more sophisticated and effective algorithms and tools. Although significant progress has been made so far, many issues still remain, resulting in the need for the development of novel approaches