Offshore Measurements of Ocean Waves using Stereo Vision Systems

In recent years, remote sensing imaging systems for the measurement of oceanic sea states have attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms, which focus on sea states with wavelengths in the range of 0.01 m to 10 m. Classical epipolar techniques and modern variational methods are reviewed to reconstruct the sea surface from the stereo pairs sequentially in time. The statistical and spectral properties of the resulting observed waves are analyzed. Current improvements of the variational methods are discussed as future lines of research.

Offshore remote sensing of the ocean by stereo vision systems

In recent years, remote sensing imaging systems for the measurement of oceanic sea states have attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms, which focus on sea states with wavelengths in the range of 0.01 m to 1 m. Both traditional disparity-based systems and modern elevation-based ones are presented in a variational optimization framework: the main idea is to pose the stereoscopic reconstruction problem of the surface of the ocean in a variational setting and design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal smoothness priors. Disparity methods estimate the disparity between images as an intermediate step toward retrieving the depth of the waves with respect to the cameras, whereas elevation methods estimate the ocean surface displacements directly in 3-D space. Both techniques are used to measure ocean waves from real data collected at offshore platforms in the Black Sea (Crimean Peninsula, Ukraine) and the Northern Adriatic Sea (Venice coast, Italy). Then, the statistical and spectral properties of the resulting observed waves are analyzed. We show the advantages and disadvantages of the presented stereo vision systems and discuss future lines of research to improve their performance in critical issues such as the robustness of the camera calibration in spite of undesired variations of the camera parameters or the processing time that it takes to retrieve ocean wave measurements from the stereo videos, which are very large datasets that need to be processed efficiently to be of practical usage. Multiresolution and short-time approaches would improve efficiency and scalability of the techniques so that wave displacements are obtained in feasible times.

Vibration reduction for vision systems on board unmanned aerial vehicles using a neuro-fuzzy controller

In this paper, an intelligent control approach based on neuro-fuzzy systems performance is presented, with the objective of counteracting the vibrations that affect the low-cost vision platform onboard an unmanned aerial system of rotating nature. A scaled dynamical model of a helicopter is used to simulate vibrations on its fuselage. The impact of these vibrations on the low-cost vision system will be assessed and an intelligent control approach will be derived in order to reduce its detrimental influence. Different trials that consider a neuro-fuzzy approach as a fundamental part of an intelligent semi-active control strategy have been carried out. Satisfactory results have been achieved compared to those obtained by means of vibration reduction passive techniques.

Space-time ocean wave measurement using variational stereo vision systems

Remote sensing imaging systems for the measurement of oceanic sea states have recently attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms. Both traditional disparity-based systems and modern elevation-based ones are presented in a variational optimization framework: the main idea is to pose the stereoscopic reconstruction problem of the surface of the ocean in a variational setting and design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal smoothness priors. Disparity methods estimate the disparity between images as an intermediate step toward retrieving the depth of the waves with respect to the cameras, whereas elevation methods estimate the ocean surface displacements directly in 3-D space. Both techniques are used to measure ocean waves from real data collected at offshore platforms in the Black Sea (Crimean Peninsula, Ukraine) and the Northern Adriatic Sea (Venice coast, Italy). Then, the statistical and spectral properties of the resulting observed waves are analyzed. We show the advantages and disadvantages of the presented stereo vision systems and discuss the improvement of their performance in critical issues such as the robustness of the camera calibration in spite of undesired variations of the camera parameters.

Catadioptric panoramic stereovision for humanoid robots

This paper proposes a novel design of a reconfigurable humanoid robot head, based on biological likeness of human being so that the humanoid robot could agreeably interact with people in various everyday tasks. The proposed humanoid head has a modular and adaptive structural design and is equipped with three main components: frame, neck motion system and omnidirectional stereovision system modules. The omnidirectional stereovision system module being the last module, a motivating contribution with regard to other computer vision systems implemented in former humanoids, it opens new research possibilities for achieving human-like behaviour. A proposal for a real-time catadioptric stereovision system is presented, including stereo geometry for rectifying the system configuration and depth estimation. The methodology for an initial approach for visual servoing tasks is divided into two phases, first related to the robust detection of moving objects, their depth estimation and position calculation, and second the development of attention-based control strategies. Perception capabilities provided allow the extraction of 3D information from a wide range of visions from uncontrolled dynamic environments, and work results are illustrated through a number of experiments.

Visual Tracking, Pose Estimation, and Control for Aerial Vehicles

El principal objetivo de esta tesis es dotar a los vehículos aéreos no tripulados (UAVs, por sus siglas en inglés) de una fuente de información adicional basada en visión. Esta fuente de información proviene de cámaras ubicadas a bordo de los vehículos o en el suelo. Con ella se busca que los UAVs realicen tareas de aterrizaje o inspección guiados por visión, especialmente en aquellas situaciones en las que no haya disponibilidad de estimar la posición del vehículo con base en GPS, cuando las estimaciones de GPS no tengan la suficiente precisión requerida por las tareas a realizar, o cuando restricciones de carga de pago impidan añadir sensores a bordo de los vehículos. Esta tesis trata con tres de las principales áreas de la visión por computador: seguimiento visual y estimación visual de la pose (posición y orientación), que a su vez constituyen la base de la tercera, denominada control servo visual, que en nuestra aplicación se enfoca en el empleo de información visual para controlar los UAVs. Al respecto, esta tesis se ocupa de presentar propuestas novedosas que permitan solucionar problemas relativos al seguimiento de objetos mediante cámaras ubicadas a bordo de los UAVs, se ocupa de la estimación de la pose de los UAVs basada en información visual obtenida por cámaras ubicadas en el suelo o a bordo, y también se ocupa de la aplicación de las técnicas propuestas para solucionar diferentes problemas, como aquellos concernientes al seguimiento visual para tareas de reabastecimiento autónomo en vuelo o al aterrizaje basado en visión, entre otros. Las diversas técnicas de visión por computador presentadas en esta tesis se proponen con el fin de solucionar dificultades que suelen presentarse cuando se realizan tareas basadas en visión con UAVs, como las relativas a la obtención, en tiempo real, de estimaciones robustas, o como problemas generados por vibraciones. Los algoritmos propuestos en esta tesis han sido probados con información de imágenes reales obtenidas realizando pruebas on-line y off-line. Diversos mecanismos de evaluación han sido empleados con el propósito de analizar el desempeño de los algoritmos propuestos, entre los que se incluyen datos simulados, imágenes de vuelos reales, estimaciones precisas de posición empleando el sistema VICON y comparaciones con algoritmos del estado del arte. Los resultados obtenidos indican que los algoritmos de visión por computador propuestos tienen un desempeño que es comparable e incluso mejor al de algoritmos que se encuentran en el estado del arte. Los algoritmos propuestos permiten la obtención de estimaciones robustas en tiempo real, lo cual permite su uso en tareas de control visual. El desempeño de estos algoritmos es apropiado para las exigencias de las distintas aplicaciones examinadas: reabastecimiento autónomo en vuelo, aterrizaje y estimación del estado del UAV. Abstract The main objective of this thesis is to provide Unmanned Aerial Vehicles (UAVs) with an additional vision-based source of information extracted by cameras located either on-board or on the ground, in order to allow UAVs to develop visually guided tasks, such as landing or inspection, especially in situations where GPS information is not available, where GPS-based position estimation is not accurate enough for the task to develop, or where payload restrictions do not allow the incorporation of additional sensors on-board. This thesis covers three of the main computer vision areas: visual tracking and visual pose estimation, which are the bases the third one called visual servoing, which, in this work, focuses on using visual information to control UAVs. In this sense, the thesis focuses on presenting novel solutions for solving the tracking problem of objects when using cameras on-board UAVs, on estimating the pose of the UAVs based on the visual information collected by cameras located either on the ground or on-board, and also focuses on applying these proposed techniques for solving different problems, such as visual tracking for aerial refuelling or vision-based landing, among others. The different computer vision techniques presented in this thesis are proposed to solve some of the frequently problems found when addressing vision-based tasks in UAVs, such as obtaining robust vision-based estimations at real-time frame rates, and problems caused by vibrations, or 3D motion. All the proposed algorithms have been tested with real-image data in on-line and off-line tests. Different evaluation mechanisms have been used to analyze the performance of the proposed algorithms, such as simulated data, images from real-flight tests, publicly available datasets, manually generated ground truth data, accurate position estimations using a VICON system and a robotic cell, and comparison with state of the art algorithms. Results show that the proposed computer vision algorithms obtain performances that are comparable to, or even better than, state of the art algorithms, obtaining robust estimations at real-time frame rates. This proves that the proposed techniques are fast enough for vision-based control tasks. Therefore, the performance of the proposed vision algorithms has shown to be of a standard appropriate to the different explored applications: aerial refuelling and landing, and state estimation. It is noteworthy that they have low computational overheads for vision systems.

A Vision-based Quadrotor Multi-robot Solution for the Indoor Autonomy Challenge of the 2013 International Micro Air Vehicle Competition

This paper presents a completely autonomous solution to participate in the Indoor Challenge of the 2013 International Micro Air Vehicle Competition (IMAV 2013). Our proposal is a multi-robot system with no centralized coordination whose robotic agents share their position estimates. The capability of each agent to navigate avoiding collisions is a consequence of the resulting emergent behavior. Each agent consists of a ground station running an instance of the proposed architecture that communicates over WiFi with an AR Drone 2.0 quadrotor. Visual markers are employed to sense and map obstacles and to improve the pose estimation based on Inertial Measurement Unit (IMU) and ground optical flow data. Based on our architecture, each robotic agent can navigate avoiding obstacles and other members of the multi-robot system. The solution is demonstrated and the achieved navigation performance is evaluated by means of experimental flights. This work also analyzes the capabilities of the presented solution in simulated flights of the IMAV 2013 Indoor Challenge. The performance of the CVG UPM team was awarded with the First Prize in the Indoor Autonomy Challenge of the IMAV 2013 competition.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

Application of self-organizing techniques for the distribution of heterogeneous multi-tasks in multi-robot systems

This paper focuses on the general problem of coordinating of multi-robot systems, more specifically, it addresses the self-election of heterogeneous and specialized tasks by autonomous robots. In this regard, it has proposed experimenting with two different techniques based chiefly on selforganization and emergence biologically inspired, by applying response threshold models as well as ant colony optimization. Under this approach it can speak of multi-tasks selection instead of multi-tasks allocation, that means, as the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. It has evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Response threshold models and stochastic learning automata for self-coordination of heterogeneous multi-task distribution in multi-robot systems.

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

A vision-based strategy for autonomous aerial refueling tasks

Autonomous aerial refueling is a key enabling technology for both manned and unmanned aircraft where extended flight duration or range are required. The results presented within this paper offer one potential vision-based sensing solution, together with a unique test environment. A hierarchical visual tracking algorithm based on direct methods is proposed and developed for the purposes of tracking a drogue during the capture stage of autonomous aerial refueling, and of estimating its 3D position. Intended to be applied in real time to a video stream from a single monocular camera mounted on the receiver aircraft, the algorithm is shown to be highly robust, and capable of tracking large, rapid drogue motions within the frame of reference. The proposed strategy has been tested using a complex robotic testbed and with actual flight hardware consisting of a full size probe and drogue. Results show that the vision tracking algorithm can detect and track the drogue at real-time frame rates of more than thirty frames per second, obtaining a robust position estimation even with strong motions and multiple occlusions of the drogue.

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.

Desarrollo de tecnologías de telemanipulación con alto grado de escalado orientadas a la interacción hombre-robot en entornos nucleares

Esta tesis se centra en desarrollo de tecnologías para la interacción hombre-robot en entornos nucleares de fusión. La problemática principal del sector de fusión nuclear radica en las condiciones ambientales tan extremas que hay en el interior del reactor, y la necesidad de que los equipos cumplan requisitos muy restrictivos para poder aguantar esos niveles de radiación, magnetismo, ultravacío, temperatura... Como no es viable la ejecución de tareas directamente por parte de humanos, habrá que utilizar dispositivos de manipulación remota para llevar a cabo los procesos de operación y mantenimiento. En las instalaciones de ITER es obligatorio tener un entorno controlado de extrema seguridad, que necesita de estándares validados. La definición y uso de protocolos es indispensable para regir su buen funcionamiento. Si nos centramos en la telemanipulación con algo grado de escalado, surge la necesidad de definir protocolos para sistemas abiertos que permitan la interacción entre equipos y dispositivos de diversa índole. En este contexto se plantea la definición del Protocolo de Teleoperación que permita la interconexión entre dispositivos maestros y esclavos de distinta tipología, pudiéndose comunicar bilateralmente entre sí y utilizar distintos algoritmos de control según la tarea a desempeñar. Este protocolo y su interconectividad se han puesto a prueba en la Plataforma Abierta de Teleoperación (P.A.T.) que se ha desarrollado e integrado en la ETSII UPM como una herramienta que permita probar, validar y realizar experimentos de telerrobótica. Actualmente, este Protocolo de Teleoperación se ha propuesto a través de AENOR al grupo ISO de Telerobotics como una solución válida al problema existente y se encuentra bajo revisión. Con el diseño de dicho protocolo se ha conseguido enlazar maestro y esclavo, sin embargo con los niveles de radiación tan altos que hay en ITER la electrónica del controlador no puede entrar dentro del tokamak. Por ello se propone que a través de una mínima electrónica convenientemente protegida se puedan multiplexar las señales de control que van a través del cableado umbilical desde el controlador hasta la base del robot. En este ejercicio teórico se demuestra la utilidad y viabilidad de utilizar este tipo de solución para reducir el volumen y peso del cableado umbilical en cifras aproximadas de un 90%, para ello hay que desarrollar una electrónica específica y con certificación RadHard para soportar los enormes niveles de radiación de ITER. Para este manipulador de tipo genérico y con ayuda de la Plataforma Abierta de Teleoperación, se ha desarrollado un algoritmo que mediante un sensor de fuerza/par y una IMU colocados en la muñeca del robot, y convenientemente protegidos ante la radiación, permiten calcular las fuerzas e inercias que produce la carga, esto es necesario para poder transmitirle al operador unas fuerzas escaladas, y que pueda sentir la carga que manipula, y no otras fuerzas que puedan influir en el esclavo remoto, como ocurre con otras técnicas de estimación de fuerzas. Como el blindaje de los sensores no debe ser grande ni pesado, habrá que destinar este tipo de tecnología a las tareas de mantenimiento de las paradas programadas de ITER, que es cuando los niveles de radiación están en sus valores mínimos. Por otro lado para que el operador sienta lo más fielmente posible la fuerza de carga se ha desarrollado una electrónica que mediante el control en corriente de los motores permita realizar un control en fuerza a partir de la caracterización de los motores del maestro. Además para aumentar la percepción del operador se han realizado unos experimentos que demuestran que al aplicar estímulos multimodales (visuales, auditivos y hápticos) aumenta su inmersión y el rendimiento en la consecución de la tarea puesto que influyen directamente en su capacidad de respuesta. Finalmente, y en referencia a la realimentación visual del operador, en ITER se trabaja con cámaras situadas en localizaciones estratégicas, si bien el humano cuando manipula objetos hace uso de su visión binocular cambiando constantemente el punto de vista adecuándose a las necesidades visuales de cada momento durante el desarrollo de la tarea. Por ello, se ha realizado una reconstrucción tridimensional del espacio de la tarea a partir de una cámara-sensor RGB-D, lo cual nos permite obtener un punto de vista binocular virtual móvil a partir de una cámara situada en un punto fijo que se puede proyectar en un dispositivo de visualización 3D para que el operador pueda variar el punto de vista estereoscópico según sus preferencias. La correcta integración de estas tecnologías para la interacción hombre-robot en la P.A.T. ha permitido validar mediante pruebas y experimentos para verificar su utilidad en la aplicación práctica de la telemanipulación con alto grado de escalado en entornos nucleares de fusión. Abstract This thesis focuses on developing technologies for human-robot interaction in nuclear fusion environments. The main problem of nuclear fusion sector resides in such extreme environmental conditions existing in the hot-cell, leading to very restrictive requirements for equipment in order to deal with these high levels of radiation, magnetism, ultravacuum, temperature... Since it is not feasible to carry out tasks directly by humans, we must use remote handling devices for accomplishing operation and maintenance processes. In ITER facilities it is mandatory to have a controlled environment of extreme safety and security with validated standards. The definition and use of protocols is essential to govern its operation. Focusing on Remote Handling with some degree of escalation, protocols must be defined for open systems to allow interaction among different kind of equipment and several multifunctional devices. In this context, a Teleoperation Protocol definition enables interconnection between master and slave devices from different typologies, being able to communicate bilaterally one each other and using different control algorithms depending on the task to perform. This protocol and its interconnectivity have been tested in the Teleoperation Open Platform (T.O.P.) that has been developed and integrated in the ETSII UPM as a tool to test, validate and conduct experiments in Telerobotics. Currently, this protocol has been proposed for Teleoperation through AENOR to the ISO Telerobotics group as a valid solution to the existing problem, and it is under review. Master and slave connection has been achieved with this protocol design, however with such high radiation levels in ITER, the controller electronics cannot enter inside the tokamak. Therefore it is proposed a multiplexed electronic board, that through suitable and RadHard protection processes, to transmit control signals through an umbilical cable from the controller to the robot base. In this theoretical exercise the utility and feasibility of using this type of solution reduce the volume and weight of the umbilical wiring approximate 90% less, although it is necessary to develop specific electronic hardware and validate in RadHard qualifications in order to handle huge levels of ITER radiation. Using generic manipulators does not allow to implement regular sensors for force feedback in ITER conditions. In this line of research, an algorithm to calculate the forces and inertia produced by the load has been developed using a force/torque sensor and IMU, both conveniently protected against radiation and placed on the robot wrist. Scaled forces should be transmitted to the operator, feeling load forces but not other undesirable forces in slave system as those resulting from other force estimation techniques. Since shielding of the sensors should not be large and heavy, it will be necessary to allocate this type of technology for programmed maintenance periods of ITER, when radiation levels are at their lowest levels. Moreover, the operator perception needs to feel load forces as accurate as possible, so some current control electronics were developed to perform a force control of master joint motors going through a correct motor characterization. In addition to increase the perception of the operator, some experiments were conducted to demonstrate applying multimodal stimuli (visual, auditory and haptic) increases immersion and performance in achieving the task since it is directly correlated with response time. Finally, referring to the visual feedback to the operator in ITER, it is usual to work with 2D cameras in strategic locations, while humans use binocular vision in direct object manipulation, constantly changing the point of view adapting it to the visual needs for performing manipulation during task procedures. In this line a three-dimensional reconstruction of non-structured scenarios has been developed using RGB-D sensor instead of cameras in the remote environment. Thus a mobile virtual binocular point of view could be generated from a camera at a fixed point, projecting stereoscopic images in 3D display device according to operator preferences. The successful integration of these technologies for human-robot interaction in the T.O.P., and validating them through tests and experiments, verify its usefulness in practical application of high scaling remote handling at nuclear fusion environments.

Vision-based vehicle detection and tracking with a mobile camera using a statistical framework

En esta tesis se aborda la detección y el seguimiento automático de vehículos mediante técnicas de visión artificial con una cámara monocular embarcada. Este problema ha suscitado un gran interés por parte de la industria automovilística y de la comunidad científica ya que supone el primer paso en aras de la ayuda a la conducción, la prevención de accidentes y, en última instancia, la conducción automática. A pesar de que se le ha dedicado mucho esfuerzo en los últimos años, de momento no se ha encontrado ninguna solución completamente satisfactoria y por lo tanto continúa siendo un tema de investigación abierto. Los principales problemas que plantean la detección y seguimiento mediante visión artificial son la gran variabilidad entre vehículos, un fondo que cambia dinámicamente debido al movimiento de la cámara, y la necesidad de operar en tiempo real. En este contexto, esta tesis propone un marco unificado para la detección y seguimiento de vehículos que afronta los problemas descritos mediante un enfoque estadístico. El marco se compone de tres grandes bloques, i.e., generación de hipótesis, verificación de hipótesis, y seguimiento de vehículos, que se llevan a cabo de manera secuencial. No obstante, se potencia el intercambio de información entre los diferentes bloques con objeto de obtener el máximo grado posible de adaptación a cambios en el entorno y de reducir el coste computacional. Para abordar la primera tarea de generación de hipótesis, se proponen dos métodos complementarios basados respectivamente en el análisis de la apariencia y la geometría de la escena. Para ello resulta especialmente interesante el uso de un dominio transformado en el que se elimina la perspectiva de la imagen original, puesto que este dominio permite una búsqueda rápida dentro de la imagen y por tanto una generación eficiente de hipótesis de localización de los vehículos. Los candidatos finales se obtienen por medio de un marco colaborativo entre el dominio original y el dominio transformado. Para la verificación de hipótesis se adopta un método de aprendizaje supervisado. Así, se evalúan algunos de los métodos de extracción de características más populares y se proponen nuevos descriptores con arreglo al conocimiento de la apariencia de los vehículos. Para evaluar la efectividad en la tarea de clasificación de estos descriptores, y dado que no existen bases de datos públicas que se adapten al problema descrito, se ha generado una nueva base de datos sobre la que se han realizado pruebas masivas. Finalmente, se presenta una metodología para la fusión de los diferentes clasificadores y se plantea una discusión sobre las combinaciones que ofrecen los mejores resultados. El núcleo del marco propuesto está constituido por un método Bayesiano de seguimiento basado en filtros de partículas. Se plantean contribuciones en los tres elementos fundamentales de estos filtros: el algoritmo de inferencia, el modelo dinámico y el modelo de observación. En concreto, se propone el uso de un método de muestreo basado en MCMC que evita el elevado coste computacional de los filtros de partículas tradicionales y por consiguiente permite que el modelado conjunto de múltiples vehículos sea computacionalmente viable. Por otra parte, el dominio transformado mencionado anteriormente permite la definición de un modelo dinámico de velocidad constante ya que se preserva el movimiento suave de los vehículos en autopistas. Por último, se propone un modelo de observación que integra diferentes características. En particular, además de la apariencia de los vehículos, el modelo tiene en cuenta también toda la información recibida de los bloques de procesamiento previos. El método propuesto se ejecuta en tiempo real en un ordenador de propósito general y da unos resultados sobresalientes en comparación con los métodos tradicionales. ABSTRACT This thesis addresses on-road vehicle detection and tracking with a monocular vision system. This problem has attracted the attention of the automotive industry and the research community as it is the first step for driver assistance and collision avoidance systems and for eventual autonomous driving. Although many effort has been devoted to address it in recent years, no satisfactory solution has yet been devised and thus it is an active research issue. The main challenges for vision-based vehicle detection and tracking are the high variability among vehicles, the dynamically changing background due to camera motion and the real-time processing requirement. In this thesis, a unified approach using statistical methods is presented for vehicle detection and tracking that tackles these issues. The approach is divided into three primary tasks, i.e., vehicle hypothesis generation, hypothesis verification, and vehicle tracking, which are performed sequentially. Nevertheless, the exchange of information between processing blocks is fostered so that the maximum degree of adaptation to changes in the environment can be achieved and the computational cost is alleviated. Two complementary strategies are proposed to address the first task, i.e., hypothesis generation, based respectively on appearance and geometry analysis. To this end, the use of a rectified domain in which the perspective is removed from the original image is especially interesting, as it allows for fast image scanning and coarse hypothesis generation. The final vehicle candidates are produced using a collaborative framework between the original and the rectified domains. A supervised classification strategy is adopted for the verification of the hypothesized vehicle locations. In particular, state-of-the-art methods for feature extraction are evaluated and new descriptors are proposed by exploiting the knowledge on vehicle appearance. Due to the lack of appropriate public databases, a new database is generated and the classification performance of the descriptors is extensively tested on it. Finally, a methodology for the fusion of the different classifiers is presented and the best combinations are discussed. The core of the proposed approach is a Bayesian tracking framework using particle filters. Contributions are made on its three key elements: the inference algorithm, the dynamic model and the observation model. In particular, the use of a Markov chain Monte Carlo method is proposed for sampling, which circumvents the exponential complexity increase of traditional particle filters thus making joint multiple vehicle tracking affordable. On the other hand, the aforementioned rectified domain allows for the definition of a constant-velocity dynamic model since it preserves the smooth motion of vehicles in highways. Finally, a multiple-cue observation model is proposed that not only accounts for vehicle appearance but also integrates the available information from the analysis in the previous blocks. The proposed approach is proven to run near real-time in a general purpose PC and to deliver outstanding results compared to traditional methods.

Using the Own Flexibility of a Climbing Robot as a Double Force Sensor

Force sensors are used when interaction tasks are carried out by robots in general, and by climbing robots in particular. If the mechanics and electronics systems are contained inside the own robot, the robot becomes portable without external control. Commercial force sensors cannot be used due to limited space and weight. By selecting the links material with appropriate stiffness and placing strain gauges on the structure, the own robot flexibility can be used such as force sensor. Thus, forces applied on the robot tip can be measured without additional external devices. Only gauges and small internal electronic converters are necessary. This paper illustrates the proposed algorithm to achieve these measurements. Additionally, experimental results are presented.