119 resultados para Mobile robots


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We propose an algorithm that extracts image features that are consistent with the 3D structure of the scene. The features can be robustly tracked over multiple views and serve as vertices of planar patches that suitably represent scene surfaces, while reducing the redundancy in the description of 3D shapes. In other words, the extracted features will off er good tracking properties while providing the basis for 3D reconstruction with minimum model complexity

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This work proposes a parallel architecture for a motion estimation algorithm. It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great numbers of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. Due to its regular processing scheme, parallel implementation of correspondence problem can be an adequate approach to reduce the computation time. This work introduces parallel and real-time implementation of such low-level tasks to be carried out from the moment that the current image is acquired by the camera until the pairs of point-matchings are detected

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S’arriba a un acord entre el grup de recerca GREFEMA i ViCOROB per estudiar els propulsors de palesutilitzats fins a l’actualitat en el robot submarí Girona 500, de forma que el model creatserveixi d’eina per apoder estudiar qualsevol tipus de propulsor que es vulgui fer servir.Es crearà un model de simulació amb CFD d’ANSYS per tal de poder recrear qualsevol situació ambqualsevol model de propulsor que es vulgui emprar, estalviant en costos de compra o fabricació, a mésd’evitar un muntatge experimental que pot no ser del tot fiable.A partir de geometries de propulsors de pales comercials existents es realitzarà una simulació amb elprograma de dinàmica de fluids computacional (CFD) d’ANSYS.La informació proporcionada per l’eina de simulació es compararan amb els resultats obtinguts de formaempírica a les instal•lacions del Parc Científic i Tecnològic de la Universitat de Girona i amb el model teòric.D’aquesta forma, es comprovarà la bondat de la simulació i es validarà el model numèric utilitzat

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El grup VICOROB de la UdG té una àmplia experiència en l’àmbit dels vehicles irobots submarins, amb diferents prototips degudament validats experimentalment.L’interès d’aquest grup de recerca és anar més enllà i conèixer exactament elcomportament del vehicle dins de l’aigua.El grup VICOROB disposa d’un vehicle subaquàtic, l’anomenat GIRONA 500 que haestat dissenyat com una plataformad'investigació amb capacitat per tornara configurar-se per a moltes aplicacionsdiferents, que van des dels clàssicssonar i servei d’imatges de vídeo fins atasques d'intervenció autònomesdifícilsL’objectiu és d’aquest projecte és obtenir a partir de la geometria real del vehicleGIRONA 500 els coeficients hidrodinàmics del submarí complet i de solamentl’estructura per així conèixer l’efecte hidrodinàmic del nombre de propulsors acoblats alrespectiu vehicle aquàtic

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Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position

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Creació d’un sistema format per un algoritme genètic que permeti dissenyar de forma automática, les dades dels valors lingüístics d’un controlador fuzzy, per a un robot amb tracció diferencial. Les dades que s’han d’obtenir han de donar-li al robot, la capacitat d’arribar a un destí, evitant els obstacles que vagi trobant al llarg del camí

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This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach

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This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed

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A visual SLAM system has been implemented and optimised for real-time deployment on an AUV equipped with calibrated stereo cameras. The system incorporates a novel approach to landmark description in which landmarks are local sub maps that consist of a cloud of 3D points and their associated SIFT/SURF descriptors. Landmarks are also sparsely distributed which simplifies and accelerates data association and map updates. In addition to landmark-based localisation the system utilises visual odometry to estimate the pose of the vehicle in 6 degrees of freedom by identifying temporal matches between consecutive local sub maps and computing the motion. Both the extended Kalman filter and unscented Kalman filter have been considered for filtering the observations. The output of the filter is also smoothed using the Rauch-Tung-Striebel (RTS) method to obtain a better alignment of the sequence of local sub maps and to deliver a large-scale 3D acquisition of the surveyed area. Synthetic experiments have been performed using a simulation environment in which ray tracing is used to generate synthetic images for the stereo system

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Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping

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Un dels principals problemes de la interacció dels robots autònoms és el coneixement de l'escena. El reconeixement és fonamental per a solucionar aquest problema i permetre als robots interactuar en un escenari no controlat. En aquest document presentem una aplicació pràctica de la captura d'objectes, de la normalització i de la classificació de senyals triangulars i circulars. El sistema s'introdueix en el robot Aibo de Sony per a millorar-ne la interacció. La metodologia presentada s'ha comprobat en simulacions i problemes de categorització reals, com ara la classificació de senyals de trànsit, amb resultats molt prometedors.

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El nombre d'aplicacions dels microrobots en biomedicina creix a mesura que el seu desenvolupament avança. Entre elles hi ha les consistents a examinar cèl·lules amb microrobots cooperants. En aquest treball es presenta un prototip a escala d'aquest problema, convenientment simplificat: dos robots tracten d'agafar una pilota que representa la cèl·lula que s'examina. Com a resultat, s'ha obtingut un algorisme deliberatiu per a la resolució d'aquest problema amb robots homogenis.

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En aquest projecte s’ha estudiat el disseny d’una plataforma robòtica mòbil per un PBL (Aprenentatge Basat en Problemes) en enginyeria informàtica. El principal objectiu és introduir aquest model en l’ensenyament universitari, com a complement de diferents assignatures de primer curs. Per arribar a aconseguir aquests objectius, s’ha dissenyat i construït una plataforma robòtica, dirigida per un microcontrolador i dotada de diversos sensors per interactuar amb l’entorn. El robot permet diferents tipus de programació i esta especialment dissenyada per ser una bona experiència educativa.

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Report for the scientific sojourn at the Swiss Federal Institute of Technology Zurich, Switzerland, between September and December 2007. In order to make robots useful assistants for our everyday life, the ability to learn and recognize objects is of essential importance. However, object recognition in real scenes is one of the most challenging problems in computer vision, as it is necessary to deal with difficulties. Furthermore, in mobile robotics a new challenge is added to the list: computational complexity. In a dynamic world, information about the objects in the scene can become obsolete before it is ready to be used if the detection algorithm is not fast enough. Two recent object recognition techniques have achieved notable results: the constellation approach proposed by Lowe and the bag of words approach proposed by Nistér and Stewénius. The Lowe constellation approach is the one currently being used in the robot localization project of the COGNIRON project. This report is divided in two main sections. The first section is devoted to briefly review the currently used object recognition system, the Lowe approach, and bring to light the drawbacks found for object recognition in the context of indoor mobile robot navigation. Additionally the proposed improvements for the algorithm are described. In the second section the alternative bag of words method is reviewed, as well as several experiments conducted to evaluate its performance with our own object databases. Furthermore, some modifications to the original algorithm to make it suitable for object detection in unsegmented images are proposed.