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The cleaning robot project : aplicação do filtro de Kalman na auto-localização de um sistema robótico autónomoPinto, Fernando Pedro Vieira Freitas January 2008 (has links)
Estágio realizado no Institute of Systems and Robotics-Porto / Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 2008
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Melhoramento do desempenho do Robot de Serviço de Limpeza : comparação de desempenho de filtros de Kalman e de filtros de partículas para auto-localizaçãoMartins, João Manuel Ferreira January 2008 (has links)
Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores - Major Automação. Faculdade de Engenharia. Universidade do Porto. 2008
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Monocular visual SLAM based on Inverse depth parametrizationRivero Pindado, Víctor January 2010 (has links)
The first objective of this research has always been carry out a study of visual techniques SLAM (Simultaneous localization and mapping), specifically the type monovisual, less studied than the stereo. These techniques have been well studied in the world of robotics. These techniques are focused on reconstruct a map of the robot enviroment while maintaining its position information in that map. We chose to investigate a method to encode the points by the inverse of its depth, from the first time that the feature was observed. This method permits efficient and accurate representation of uncertainty during undelayed initialization and beyond, all within the standard extended Kalman filter (EKF).At first, the study mentioned it should be consolidated developing an application that implements this method. After suffering various difficulties, it was decided to make use of a platform developed by the same author of Slam method mentioned in MATLAB. Until then it had developed the tasks of calibration, feature extraction and matching. From that point, that application was adapted to the characteristics of our camera and our video to work. We recorded a video with our camera following a known trajectory to check the calculated path shown in the application. Corroborating works and studying the limitations and advantages of this method.
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Monocular Visual SLAMbased on Inverse DepthParametrizationMonocular Visual SLAMbased on Inverse DepthParametrizationRivero Pindado, Victor January 2010 (has links)
The first objective of this research has always been carry out a study of visual techniques SLAM (Simultaneous localization and mapping), specifically the type monovisual, less studied than the stereo. These techniques have been well studied in the world of robotics. These techniques are focused on reconstruct a map of the robot enviroment while maintaining its position information in that map. We chose to investigate a method to encode the points by the inverse of its depth, from the first time that the feature was observed. This method permits efficient and accurate representation of uncertainty during undelayed initialization and beyond, all within the standard extended Kalman filter (EKF).At first, the study mentioned it should be consolidated developing an application that implements this method. After suffering various difficulties, it was decided to make use of a platform developed by the same author of Slam method mentioned in MATLAB. Until then it had developed the tasks of calibration, feature extraction and matching. From that point, that application was adapted to the characteristics of our camera and our video to work. We recorded a video with our camera following a known trajectory to check the calculated path shown in the application. Corroborating works and studying the limitations and advantages of this method.
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Estimation and Pre-Processing of Sensor Data in Heavy Duty Vehicle PlatooningPettersson, Hanna January 2012 (has links)
Today, a rapid development towards fuel efficient technological aids for vehicles is in progress. One step towards this is the development of platooning systems. The main concept of platooning is to let several heavy duty vehicles (HDVs) drive in a convoy and share important information with each other via wireless communication. This thesis describes one out of three subsystems in a project developed to handle the process from raw sensor data to control signal. The goal of the project is to achieve a safe and smooth control with the main purpose of reduced fuel consumption. This subsystem processes the raw sensor data received from the different HDVs. The purpose is to estimate the positions and velocities of the vehicles in a platoon, taking into account that packet-loss, out of sequence measurements and irrelevant information can occur. This is achieved by filtering the information from different sensors in an Extended Kalman Filter and converting it into a local coordinate system with the origin in the ego vehicle. Moreover, the estimates are sorted and categorized into classes with respect to the status of the vehicles. The result of the thesis is useful estimates that are independent of outer effects in a local reference system with origin in the host vehicle. This information can then be used for further sensor fusion and implementation of a Model Predictive Controller (MPC) in two other subsystems. These three subsystems result in a smooth and safe control with an average reduced fuel consumption of approxi- mately 11.1% when the vehicles drive with a distance of 0.5 seconds in a simulated environment. / Dagens utveckling inom fordonsindustrin fokuserar mer och mer påutveckling av bränsleeffektiva hjälpmedel. Ett steg i denna riktning är utvecklingen av platooningsystem. Huvudkonceptet med platooning är att låta flera tunga fordon köra i följd i en konvoj och dela viktig information med varandra via trådlös kommuni- kation och en automatiserad styrstrategi. Detta examensarbete beskriver ett utav tre delsystem i ett projekt som är utvecklat för att hantera en process från rå sensordata till styrsignaler för fordonen. Målet är att uppnå en säker och mjuk reglering med huvudsyftet att reducera bränsleförbrukningen. Det här delsystemet behandlar mottagen sensordata från de olika fordonen. Målet med delsystemet är att skatta positioner och hastigheter för fordonen i konvojen med hänsyn till att förlorad, försenad eller irrelevant information från det trådlösa nätverket kan förekomma. Detta uppnås genom filtrering i ett Extended Kalman Filter och konvertering till ett lokalt referenssystem med origo i det egna fordo- net. Utöver detta sorteras informationen och kategoriseras in i olika klasser efter fordonens status. Examensarbetet resulterade i användbara skattningar oberoende av yttre om- ständigheter i ett lokalt referenssystem med origo i det egna fordonet. Denna information kan användas vidare för ytterligare sensorfusion och implementering av en modellbaserad prediktionsregulator (MPC) i två andra delsystem. De tre delsystemen resulterade i en mjuk och säker reglering och en reducerad bränsleför- brukning med i genomsnitt 11.1% då fordonen körde med 0.5 sekunders avstånd i en simulerad miljö.
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Investigations of Channel Estimation Using Kalman Filter for OFDM Systems in Time Varying ChannelChou, Hsin-Heng 23 August 2006 (has links)
In this thesis, a modified Kalman filter is proposed for time varying channel estimation in orthogonal frequency division multiplexing (OFDM). The proposed scheme adopts pre-coding scheme and minimum mean squared error (MMSE) equalizer to improve system performance. By using pre-coding schemes, information can be protected by signal diversities, which prevent Kalman filter to disperse due to erroneous data signals. In this investigation, the proposed system architecture is verified by using simulation experiments. Simulation results demonstrate that the proposed schemes substantially improve system performances under verious channel conditions.
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Video Restoration Based on Kalman FilteringHung, Shau-Pin 10 July 2001 (has links)
In this paper, we propose a Kalman filtering method to restore signal when both the digital and analog signal are available. The digital video signal is coded by method of MPEG. The error can be introduced in the quantization process of the block DCT transformation. So the quality of the image from the digital video signal needs to be improved. Considering the analog video signal is corrupted by the Gauss White Noise. We can apply the Kalman filter to these two signals at the same time to restore the image for a better quality.
The image structure is defined to be the linear relationship between pixels with their upper and left neighbors. So we can determinate the image structure property by the linear equations of the pixel gray level. Generally, the image segmentation takes the gray values as the property. In our case we take the linear equations as our property function. This property implies an abstract concept and can¡¦t measure directly. We determine the unity of the image structure by measuring the error from merging the pixel into one region. We achieve a recursive formula for computing the error by the sequential least square error method.
In the signal processing, Kalman filter is used for optimal estimation of the signal corrupted by additive noise. We segment the image by its local property. By our segmentation technique every region has its specific image structure. The structures are system parameters of Kalman filter.
We first utilize the method of segmentation on the image recovered from the MPEG signal to find the local parameters. The results of experiments show that we can improve the images quality when the MPEG signal is not very good.
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Navigation solution for the Texas A&M autonomous ground vehicleOdom, Craig Allen 30 October 2006 (has links)
The need addressed in this thesis is to provide an Autonomous Ground Vehicle (AGV)
with accurate information regarding its position, velocity, and orientation. The system chosen to
meet these needs incorporates (1) a differential Global Positioning System, (2) an Inertial
Measurement Unit consisting of accelerometers and angular-rate sensors, and (3) a Kalman
Filter (KF) to fuse the sensor data. The obstacle avoidance software requires position and
orientation to build a global map of obstacles based on the returns of a scanning laser
rangefinder. The path control software requires position and velocity.
The development of the KF is the major contribution of this thesis. This technology can
either be purchased or developed, and, for educational and financial reasons, it was decided to
develop instead of purchasing the KF software. This thesis analyzes three different cases of
navigation: one-dimensional, two dimensional and three-dimensional (general). Each becomes
more complex, and separating them allows a three step progression to reach the general motion
solution.
Three tests were conducted at the Texas A&M University Riverside campus that
demonstrated the accuracy of the solution. Starting from a designated origin, the AGV traveled
along the runway and then returned to the same origin within 11 cm along the North axis, 19 cm
along the East axis and 8 cm along the Down axis. Also, the vehicle traveled along runway 35R
which runs North-South within 0.1ð, with the yaw solution consistently within 1ð of North or
South. The final test was mapping a box onto the origin of the global map, which requires
accurate linear and angular position estimates and a correct mapping transformation.
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Modélisation électrique et énergétique des accumulateurs Li-Ion. Estimation en ligne de la SOC et de la SOHUrbain, Matthieu Davat, Bernard Rael, Stéphane January 2009 (has links) (PDF)
Thèse de doctorat : Génie électrique : INPL : 2009. / Titre provenant de l'écran-titre.
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ASW fusion on a PC /Mann, Joelle J. January 2004 (has links) (PDF)
Thesis (M.S. in Applied Science (Operations Research))--Naval Postgraduate School, June 2004. / Thesis advisor(s): Alan Washburn. Includes bibliographical references (p. 49-50). Also available online.
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