931 resultados para Visual robot control
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In this paper, a trajectory tracking control problem for a nonholonomic mobile robot by the integration of a kinematic neural controller (KNC) and a torque neural controller (TNC) is proposed, where both the kinematic and dynamic models contains disturbances. The KNC is a variable structure controller (VSC) based on the sliding mode control theory (SMC), and applied to compensate the kinematic disturbances. The TNC is a inertia-based controller constituted of a dynamic neural controller (DNC) and a robust neural compensator (RNC), and applied to compensate the mobile robot dynamics, and bounded unknown disturbances. Stability analysis with basis on Lyapunov method and simulations results are provided to show the effectiveness of the proposed approach. © 2012 Springer-Verlag.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The goal of this study was to investigate the effects of manipulation of the characteristics of visual stimulus on postural control in dyslexic children. A total of 18 dyslexic and 18 non-dyslexic children stood upright inside a moving room, as still as possible, and looked at a target at different conditions of distance between the participant and a moving room frontal wall (25-150 cm) and vision (full and central). The first trial was performed without vision (baseline). Then four trials were performed in which the room remained stationary and eight trials with the room moving, lasting 60 s each. Mean sway amplitude, coherence, relative phase, and angular deviation were calculated. The results revealed that dyslexic children swayed with larger magnitude in both stationary and moving conditions. When the room remained stationary, all children showed larger body sway magnitude at 150 cm distance. Dyslexic children showed larger body sway magnitude in central compared to full vision condition. In the moving condition, body sway magnitude was similar between dyslexic and non-dyslexic children but the coupling between visual information and body sway was weaker in dyslexic children. Moreover, in the absence of peripheral visual cues, induced body sway in dyslexic children was temporally delayed regarding visual stimulus. Taken together, these results indicate that poor postural control performance in dyslexic children is related to how sensory information is acquired from the environment and used to produce postural responses. In conditions in which sensory cues are less informative, dyslexic children take longer to process sensory stimuli in order to obtain precise information, which leads to performance deterioration. (C) 2014 Elsevier Ltd. All rights reserved.
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This thesis deals with Visual Servoing and its strictly connected disciplines like projective geometry, image processing, robotics and non-linear control. More specifically the work addresses the problem to control a robotic manipulator through one of the largely used Visual Servoing techniques: the Image Based Visual Servoing (IBVS). In Image Based Visual Servoing the robot is driven by on-line performing a feedback control loop that is closed directly in the 2D space of the camera sensor. The work considers the case of a monocular system with the only camera mounted on the robot end effector (eye in hand configuration). Through IBVS the system can be positioned with respect to a 3D fixed target by minimizing the differences between its initial view and its goal view, corresponding respectively to the initial and the goal system configurations: the robot Cartesian Motion is thus generated only by means of visual informations. However, the execution of a positioning control task by IBVS is not straightforward because singularity problems may occur and local minima may be reached where the reached image is very close to the target one but the 3D positioning task is far from being fulfilled: this happens in particular for large camera displacements, when the the initial and the goal target views are noticeably different. To overcame singularity and local minima drawbacks, maintaining the good properties of IBVS robustness with respect to modeling and camera calibration errors, an opportune image path planning can be exploited. This work deals with the problem of generating opportune image plane trajectories for tracked points of the servoing control scheme (a trajectory is made of a path plus a time law). The generated image plane paths must be feasible i.e. they must be compliant with rigid body motion of the camera with respect to the object so as to avoid image jacobian singularities and local minima problems. In addition, the image planned trajectories must generate camera velocity screws which are smooth and within the allowed bounds of the robot. We will show that a scaled 3D motion planning algorithm can be devised in order to generate feasible image plane trajectories. Since the paths in the image are off-line generated it is also possible to tune the planning parameters so as to maintain the target inside the camera field of view even if, in some unfortunate cases, the feature target points would leave the camera images due to 3D robot motions. To test the validity of the proposed approach some both experiments and simulations results have been reported taking also into account the influence of noise in the path planning strategy. The experiments have been realized with a 6DOF anthropomorphic manipulator with a fire-wire camera installed on its end effector: the results demonstrate the good performances and the feasibility of the proposed approach.
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This thesis deals with distributed control strategies for cooperative control of multi-robot systems. Specifically, distributed coordination strategies are presented for groups of mobile robots. The formation control problem is initially solved exploiting artificial potential fields. The purpose of the presented formation control algorithm is to drive a group of mobile robots to create a completely arbitrarily shaped formation. Robots are initially controlled to create a regular polygon formation. A bijective coordinate transformation is then exploited to extend the scope of this strategy, to obtain arbitrarily shaped formations. For this purpose, artificial potential fields are specifically designed, and robots are driven to follow their negative gradient. Artificial potential fields are then subsequently exploited to solve the coordinated path tracking problem, thus making the robots autonomously spread along predefined paths, and move along them in a coordinated way. Formation control problem is then solved exploiting a consensus based approach. Specifically, weighted graphs are used both to define the desired formation, and to implement collision avoidance. As expected for consensus based algorithms, this control strategy is experimentally shown to be robust to the presence of communication delays. The global connectivity maintenance issue is then considered. Specifically, an estimation procedure is introduced to allow each agent to compute its own estimate of the algebraic connectivity of the communication graph, in a distributed manner. This estimate is then exploited to develop a gradient based control strategy that ensures that the communication graph remains connected, as the system evolves. The proposed control strategy is developed initially for single-integrator kinematic agents, and is then extended to Lagrangian dynamical systems.
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BACKGROUND It has been suggested that sleep apnea syndrome may play a role in normal-tension glaucoma contributing to optic nerve damage. The purpose of this study was to evaluate if optic nerve and visual field parameters in individuals with sleep apnea syndrome differ from those in controls. PATIENTS AND METHODS From the records of the sleep laboratory at the University Hospital in Bern, Switzerland, we recruited consecutive patients with severe sleep apnea syndrome proven by polysomnography, apnea-hypopnea index >20, as well as no sleep apnea controls with apnea-hypopnea index <10. Participants had to be unknown to the ophtalmology department and had to have no recent eye examination in the medical history. All participants underwent a comprehensive eye examination, scanning laser polarimetry (GDx VCC, Carl Zeiss Meditec, Dublin, California), scanning laser ophthalmoscopy (Heidelberg Retina Tomograph II, HRT II), and automated perimetry (Octopus 101 Programm G2, Haag-Streit Diagnostics, Koeniz, Switzerland). Mean values of the parameters of the two groups were compared by t-test. RESULTS The sleep apnea group consisted of 69 eyes of 35 patients; age 52.7 ± 9.7 years, apnea-hypopnea index 46.1 ± 24.8. As controls served 38 eyes of 19 patients; age 45.8 ± 11.2 years, apnea-hypopnea index 4.8 ± 1.9. A difference was found in mean intraocular pressure, although in a fully overlapping range, sleep apnea group: 15.2 ± 3.1, range 8-22 mmHg, controls: 13.6 ± 2.3, range 9-18 mmHg; p<0.01. None of the extended visual field, optic nerve head (HRT) and retinal nerve fiber layer (GDx VCC) parameters showed a significant difference between the groups. CONCLUSION Visual field, optic nerve head, and retinal nerve fiber layer parameters in patients with sleep apnea did not differ from those in the control group. Our results do not support a pathogenic relationship between sleep apnea syndrome and glaucoma.
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The goal of the work described in this paper is to develop a visual line guided system for being used on-board an Autonomous Guided Vehicle (AGV) commercial car, controlling the steering and using just the visual information of a line painted below the car. In order to implement the control of the vehicle, a Fuzzy Logic controller has been implemented, that has to be robust against curvature changes and velocity changes. The only input information for the controller is the visual distance from the image center captured by a camera pointing downwards to the guiding line on the road, at a commercial frequency of 30Hz. The good performance of the controller has successfully been demonstrated in a real environment at urban velocities. The presented results demonstrate the capability of the Fuzzy controller to follow a circuit in urban environments without previous information about the path or any other information from additional sensors
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In this paper, two techniques to control UAVs (Unmanned Aerial Vehicles), based on visual information are presented. The first one is based on the detection and tracking of planar structures from an on-board camera, while the second one is based on the detection and 3D reconstruction of the position of the UAV based on an external camera system. Both strategies are tested with a VTOL (Vertical take-off and landing) UAV, and results show good behavior of the visual systems (precision in the estimation and frame rate) when estimating the helicopter¿s position and using the extracted information to control the UAV.
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El objetivo principal de esta Tesis es extender la utilización del “Soft- Computing” para el control de vehículos sin piloto utilizando visión. Este trabajo va más allá de los típicos sistemas de control utilizados en entornos altamente controlados, demonstrando la fuerza y versatilidad de la lógica difusa (Fuzzy Logic) para controlar vehículos aéreos y terrestres en un abanico de applicaciones diferentes. Para esta Tesis se ha realizado un gran número de pruebas reales en las cuales los controladores difusos han manejado una plataforma visual “pan-and-tilt”, un helicoptero, un coche comercial y hasta dos tipos de quadrirotores. El uso del método de optimización “Cross-Entropy” ha sido utilizado para mejorar el comportamiento de algunos de los controladores borrosos. Todos los controladores difusos presentados en ésta Tesis han sido implementados utilizando un código desarrollado por el candidato para tal efecto, llamado MOFS (Miguel Olivares’ Fuzzy Software). Diferentes algoritmos visuales han sido utilizados para adquirir la informaci´on visual del entorno, “Cmashift”, descomposición de la homografía y detección de marcas de realidad aumentada, entre otros. Dicha información visual ha sido utilizada como entrada de los controladores difusos para comandar los vehículos en las diferentes applicaciones autonomas. El volante de un vehículo comercial ha sido controlado para realizar pruebas de conducción autónoma en condiciones de tráfico similares a las de una ciudad. El sistema ha llegado a completar con éxito pruebas de más de 6 km sin ninguna interacción humana, mediante el seguimiento de una línea pintada en el suelo. El limitado campo visual del sistema no ha sido impedimento para alcanzar velocidades de hasta 48 km/h y ser guiado autonomamente en curvas de radio reducido. Objetos estáticos y móviles han sido seguidos desde un helicoptero no tripulado, mediante el control de una plataforma visual “pan-and-tilt”. ´Éste mismo helicoptero ha sido controlado completamente para su aterrizaje autonomo, mediante el control del movimiento lateral (roll), horizontal (pitch) y de altitud. El seguimiento de objetos volantes ha sido resulto mediante el control horizontal (pitch) y de orientación (heading) de un quadrirotor. Para tareas de evitación de obstáculos se ha implementado un controlador difuso para el manejo de la orientación (heading) de un quadrirotor. En el campo de la optimización de controladores se ha aportado al estado del arte una extensión del uso del método “Cross-Entropy”. Está Tesis presenta una novedosa implementación de dicho método para la optimización de las ganancias, la posición y medida de los conjuntos de las funciones de pertenecia y el peso de las reglas para mejorar el comportamiento de un controlador difuso. Dichos procesos de optimización se han realizado utilizando “ROS” y “Matlab Simulink” para obtener mejores resultados para la evitación de colisiones con vehículos aéreos no tripulados. Ésta Tesis demuestra que los controladores implementados con lógica difusa son altamente capaces de controlador sistemas sin tener en cuenta el modelo del vehículo a controlador en entornos altamente perturbables con un sensor de bajo coste como es una cámara. El ruido presentes causado por los cambios de iluminación en la adquisición de imágenes y la alta incertidumbre en la detección visual han sido manejados satisfactoriamente por ésta técnica de de “Soft-Computing” para distintas aplicaciones tanto con vehículos aéreos como terrestres.
Diseño, construcción y control de un robot doméstico para asistencia y entrenamiento de la movilidad
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Esta tesis presenta el diseño conceptual, el análisis y la planificación de movimientos de un robot de asistencia domestica. El objetivo de este robot es ayudar a personas con problemas de movilidad, las cuales les impiden tener una vida independiente. Se realiza una investigación para identificar las principales necesidades de ayuda técnica y una revisión del estado del arte de robots de asistencia y rehabilitación. Esta información es empleada durante el proceso del diseño conceptual para establecer los objetivos del diseño identificar y las soluciones previamente propuestas. Posteriormente, se presenta la propuesta de un robot asistente para la marcha y el levantado de la posición de sentado, cuyo diseño permite al usuario realizar sus actividades de la vida diaria. Para evaluar diversos aspectos del concepto se desarrollo un prototipo a escala. Este prototipo fue útil para establecer la arquitectura de control del robot y probar el principio de funcionamiento de diversos elementos del concepto. Se propone la manera de controlar la ejecución de tareas y de navegación del robot, se simula y se analiza a través de las redes de Petri, se implementa y se prueba en el prototipo a escala. Se desarrollo el modelado dinámico y cinemático del robot. Se propone una relación entre la cinemática del movimiento de levantado normal de una persona y la cinemática del robot para generar las trayectorias a ejecutar por los actuadores. Mediante una herramienta de simulación se realizo un estudio de las fuerzas internas que se llevan a cabo en el usuario y en el robot durante la tarea de levantado. En este punto, se analizo la capacidad del robot para minimizar la fuerza que se ejerce en las articulaciones en la persona.
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The objective of this paper is to design a path following control system for a car-like mobile robot using classical linear control techniques, so that it adapts on-line to varying conditions during the trajectory following task. The main advantages of the proposed control structure is that well known linear control theory can be applied in calculating the PID controllers to full control requirements, while at the same time it is exible to be applied in non-linear changing conditions of the path following task. For this purpose the Frenet frame kinematic model of the robot is linearised at a varying working point that is calculated as a function of the actual velocity, the path curvature and kinematic parameters of the robot, yielding a transfer function that varies during the trajectory. The proposed controller is formed by a combination of an adaptive PID and a feed-forward controller, which varies accordingly with the working conditions and compensates the non-linearity of the system. The good features and exibility of the proposed control structure have been demonstrated through realistic simulations that include both kinematics and dynamics of the car-like robot.
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Rapid prototyping environments can speed up the research of visual control algorithms. We have designed and implemented a software framework for fast prototyping of visual control algorithms for Micro Aerial Vehicles (MAV). We have applied a combination of a proxy-based network communication architecture and a custom Application Programming Interface. This allows multiple experimental configurations, like drone swarms or distributed processing of a drone’s video stream. Currently, the framework supports a low-cost MAV: the Parrot AR.Drone. Real tests have been performed on this platform and the results show comparatively low figures of the extra communication delay introduced by the framework, while adding new functionalities and flexibility to the selected drone. This implementation is open-source and can be downloaded from www.vision4uav.com/?q=VC4MAV-FW
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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.
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En este Trabajo Fin de Grado se aborda la concepción, diseño, desarrollo y testeo de un robot esférico. En el se cubre el diseño mecánico y su fabricación, el modelado dinámico y su control, y el diseño hardware y software.