191 resultados para Slam
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PEDROSA, Diogo P. F. ; MEDEIROS, Adelardo A. D. ; ALSINA, Pablo J. . Uma Proposta de SLAM com Determinação de Informações Geométricas do Ambiente. In: CONGRESSO BRASILEIRO DE AUTOMÁTICA, 16, Salvador, BA, 2006. Anais... Salvador: CBA, 2006. v. 1. p. 1704-1709
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SANTANA, André M.; SANTIAGO, Gutemberg S.; MEDEIROS, Adelardo A. D. Real-Time Visual SLAM Using Pre-Existing Floor Lines as Landmarks and a Single Camera. In: CONGRESSO BRASILEIRO DE AUTOMÁTICA, 2008, Juiz de Fora, MG. Anais... Juiz de Fora: CBA, 2008.
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This work intends to show a new and few explored SLAM approach inside the simultaneous localization and mapping problem (SLAM). The purpose is to put a mobile robot to work in an indoor environment. The robot should map the environment and localize itself in the map. The robot used in the tests has an upward camera and encoders on the wheels. The landmarks in this built map are light splotches on the images of the camera caused by luminaries on the ceil. This work develops a solution based on Extended Kalman Filter to the SLAM problem using a developed observation model. Several developed tests and softwares to accomplish the SLAM experiments are shown in details
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Morbillivirus cell entry is controlled by hemagglutinin (H), an envelope-anchored viral glycoprotein determining interaction with multiple host cell surface receptors. Subsequent to virus-receptor attachment, H is thought to transduce a signal triggering the viral fusion glycoprotein, which in turn drives virus-cell fusion activity. Cell entry through the universal morbillivirus receptor CD150/SLAM was reported to depend on two nearby microdomains located within the hemagglutinin. Here, we provide evidence that three key residues in the virulent canine distemper virus A75/17 H protein (Y525, D526, and R529), clustering at the rim of a large recessed groove created by beta-propeller blades 4 and 5, control SLAM-binding activity without drastically modulating protein surface expression or SLAM-independent F triggering.
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Comunicación presentada en el XI Workshop of Physical Agents, Valencia, 9-10 septiembre 2010.
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Comunicación presentada en el X Workshop of Physical Agents, Cáceres, 10-11 septiembre 2009.
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Comunicación presentada en el X Workshop of Physical Agents, Cáceres, 10-11 septiembre 2009.
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Several works deal with 3D data in SLAM problem. Data come from a 3D laser sweeping unit or a stereo camera, both providing a huge amount of data. In this paper, we detail an efficient method to extract planar patches from 3D raw data. Then, we use these patches in an ICP-like method in order to address the SLAM problem. Using ICP with planes is not a trivial task. It needs some adaptation from the original ICP. Some promising results are shown for outdoor environment.
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Paper submitted to the 43rd International Symposium on Robotics (ISR), Taipei, Taiwan, August 29-31, 2012.
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Paper submitted to the 39th International Symposium on Robotics ISR 2008, Seoul, South Korea, October 15-17, 2008.
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Nowadays, the use of RGB-D sensors have focused a lot of research in computer vision and robotics. These kinds of sensors, like Kinect, allow to obtain 3D data together with color information. However, their working range is limited to less than 10 meters, making them useless in some robotics applications, like outdoor mapping. In these environments, 3D lasers, working in ranges of 20-80 meters, are better. But 3D lasers do not usually provide color information. A simple 2D camera can be used to provide color information to the point cloud, but a calibration process between camera and laser must be done. In this paper we present a portable calibration system to calibrate any traditional camera with a 3D laser in order to assign color information to the 3D points obtained. Thus, we can use laser precision and simultaneously make use of color information. Unlike other techniques that make use of a three-dimensional body of known dimensions in the calibration process, this system is highly portable because it makes use of small catadioptrics that can be placed in a simple manner in the environment. We use our calibration system in a 3D mapping system, including Simultaneous Location and Mapping (SLAM), in order to get a 3D colored map which can be used in different tasks. We show that an additional problem arises: 2D cameras information is different when lighting conditions change. So when we merge 3D point clouds from two different views, several points in a given neighborhood could have different color information. A new method for color fusion is presented, obtaining correct colored maps. The system will be tested by applying it to 3D reconstruction.