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Thematische Bibliographien / Odometry estimation / Dissertationen

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Dissertationen zum Thema „Odometry estimation“

Autor: Grafiati

Veröffentlicht am 28. Juni 2021

Zuletzt aktualisiert am 13. Februar 2022

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1

Masson, Clément. "Direction estimation using visual odometry." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169377.

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This Master thesis tackles the problem of measuring objects’ directions from a motionlessobservation point. A new method based on a single rotating camera requiring the knowledge ofonly two (or more) landmarks’ direction is proposed. In a first phase, multi-view geometry isused to estimate camera rotations and key elements’ direction from a set of overlapping images.Then in a second phase, the direction of any object can be estimated by resectioning the cameraassociated to a picture showing this object. A detailed description of the algorithmic chain isgiven, along with test results on both sy

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2

Holmqvist, Niclas. "HANDHELD LIDAR ODOMETRY ESTIMATION AND MAPPING SYSTEM." Thesis, Mälardalens högskola, Inbyggda system, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-41137.

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Ego-motion sensors are commonly used for pose estimation in Simultaneous Localization And Mapping (SLAM) algorithms. Inertial Measurement Units (IMUs) are popular sensors but suffer from integration drift over longer time scales. To remedy the drift they are often used in combination with additional sensors, such as a LiDAR. Pose estimation is used when scans, produced by these additional sensors, are being matched. The matching of scans can be computationally heavy as one scan can contain millions of data points. Methods exist to simplify the problem of finding the relative pose between senso

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3

CHEN, HONGYI. "GPS-oscillation-robust Localization and Visionaided Odometry Estimation." Thesis, KTH, Maskinkonstruktion (Inst.), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-247299.

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GPS/IMU integrated systems are commonly used for vehicle navigation. The algorithm for this coupled system is normally based on Kalman filter. However, oscillated GPS measurements in the urban environment can lead to localization divergence easily. Moreover, heading estimation may be sensitive to magnetic interference if it relies on IMU with integrated magnetometer. This report tries to solve the localization problem on GPS oscillation and outage, based on adaptive extended Kalman filter(AEKF). In terms of the heading estimation, stereo visual odometry(VO) is fused to overcome the effect by m

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4

Rao, Anantha N. "Learning-based Visual Odometry - A Transformer Approach." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627658636420617.

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5

Awang, Salleh Dayang Nur Salmi Dharmiza. "Study of vehicle localization optimization with visual odometry trajectory tracking." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS601.

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Au sein des systèmes avancés d’aide à la conduite (Advanced Driver Assistance Systems - ADAS) pour les systèmes de transport intelligents (Intelligent Transport Systems - ITS), les systèmes de positionnement, ou de localisation, du véhicule jouent un rôle primordial. Le système GPS (Global Positioning System) largement employé ne peut donner seul un résultat précis à cause de facteurs extérieurs comme un environnement contraint ou l’affaiblissement des signaux. Ces erreurs peuvent être en partie corrigées en fusionnant les données GPS avec des informations supplémentaires provenant d'autres ca

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6

Ay, Emre. "Ego-Motion Estimation of Drones." Thesis, KTH, Robotik, perception och lärande, RPL, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210772.

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To remove the dependency on external structure for drone positioning in GPS-denied environments, it is desirable to estimate the ego-motion of drones on-board. Visual positioning systems have been studied for quite some time and the literature on the area is diligent. The aim of this project is to investigate the currently available methods and implement a visual odometry system for drones which is capable of giving continuous estimates with a lightweight solution. In that manner, the state of the art systems are investigated and a visual odometry system is implemented based on the design deci

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7

Lee, Hong Yun. "Deep Learning for Visual-Inertial Odometry: Estimation of Monocular Camera Ego-Motion and its Uncertainty." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu156331321922759.

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8

Ringdahl, Viktor. "Stereo Camera Pose Estimation to Enable Loop Detection." Thesis, Linköpings universitet, Datorseende, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-154392.

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Visual Simultaneous Localization And Mapping (SLAM) allows for three dimensionalreconstruction from a camera’s output and simultaneous positioning of the camera withinthe reconstruction. With use cases ranging from autonomous vehicles to augmentedreality, the SLAM field has garnered interest both commercially and academically. A SLAM system performs odometry as it estimates the camera’s movement throughthe scene. The incremental estimation of odometry is not error free and exhibits driftover time with map inconsistencies as a result. Detecting the return to a previously seenplace, a loop, mean

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9

Ready, Bryce Benson. "Filtering Techniques for Pose Estimation with Applications to Unmanned Air Vehicles." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3490.

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This work presents two novel methods of estimating the state of a dynamic system in a Kalman Filtering framework. The first is an application specific method for use with systems performing Visual Odometry in a mostly planar scene. Because a Visual Odometry method inherently provides relative information about the pose of a platform, we use this system as part of the time update in a Kalman Filtering framework, and develop a novel way to propagate the uncertainty of the pose through this time update method. Our initial results show that this method is able to reduce localization error signific

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10

Kim, Jae-Hak, and Jae-Hak Kim@anu edu au. "Camera Motion Estimation for Multi-Camera Systems." The Australian National University. Research School of Information Sciences and Engineering, 2008. http://thesis.anu.edu.au./public/adt-ANU20081211.011120.

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The estimation of motion of multi-camera systems is one of the most important tasks in computer vision research. Recently, some issues have been raised about general camera models and multi-camera systems. Using many cameras as a single camera is studied [60], and the epipolar geometry constraints of general camera models is theoretically derived. Methods for calibration, including a self-calibration method for general camera models, are studied [78, 62]. Multi-camera systems are an example of practically implementable general camera models and they are widely used in many applications nowaday

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11

Li, Diya. "Simultaneous Three-Dimensional Mapping and Geolocation of Road Surface." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/85470.

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This thesis paper presents a simultaneous 3D mapping and geolocation of road surface technique that combines local road surface mapping and global camera localization. The local road surface is generated by structure from motion (SFM) with multiple views and optimized by Bundle Adjustment (BA). A system is developed for the global reconstruction of 3D road surface. Using the system, the proposed technique globally reconstructs 3D road surface by estimating the global camera pose using the Adaptive Extended Kalman Filter (AEKF) and integrates it with local road surface reconstruction technique

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12

Dill, Evan T. "GPS/Optical/Inertial Integration for 3D Navigation and Mapping Using Multi-copter Platforms." Ohio University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1427382541.

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13

Janíček, Kryštof. "Odhad rychlosti vozidla ze záznamu on-board kamery." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2018. http://www.nusl.cz/ntk/nusl-385901.

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This thesis describes the design and implementation of system for vehicle speed estimation from on-board camera recording. Speed estimation is based on optical flow estimation and convolutional neural network. Designed system is able to estimate speed with average error of 20% on created data set where actual speed is greater than 35 kilometers per hour.

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14

Svoboda, Ondřej. "Analýza vlastností stereokamery ZED ve venkovním prostředí." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-399416.

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The Master thesis is focused on analyzing stereo camera ZED in the outdoor environment. There is compared ZEDfu visual odometry with commonly used methods like GPS or wheel odometry. Moreover, the thesis includes analyses of SLAM in the changeable outdoor environment, too. The simultaneous mapping and localization in RTAB-Map were processed separately with SIFT and BRISK descriptors. The aim of this master thesis is to analyze the behaviour ZED camera in the outdoor environment for future implementation in mobile robotics.

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15

Pedreira, Carabel Carlos Javier. "Terrain Mapping for Autonomous Vehicles." Thesis, KTH, Datorseende och robotik, CVAP, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-174132.

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Autonomous vehicles have become the forefront of the automotive industry nowadays, looking to have safer and more efficient transportation systems. One of the main issues for every autonomous vehicle consists in being aware of its position and the presence of obstacles along its path. The current project addresses the pose and terrain mapping problem integrating a visual odometry method and a mapping technique. An RGB-D camera, the Kinect v2 from Microsoft, was chosen as sensor for capturing information from the environment. It was connected to an Intel mini-PC for real-time processing. Both p

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16

Ellingson, Gary James. "Cooperative Navigation of Fixed-Wing Micro Air Vehicles in GPS-Denied Environments." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/8706.

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Micro air vehicles have recently gained popularity due to their potential as autonomous systems. Their future impact, however, will depend in part on how well they can navigate in GPS-denied and GPS-degraded environments. In response to this need, this dissertation investigates a potential solution for GPS-denied operations called relative navigation. The method utilizes keyframe-to-keyframe odometry estimates and their covariances in a global back end that represents the global state as a pose graph. The back end is able to effectively represent nonlinear uncertainties and incorporate opportu

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17

Jackson, James Scott. "Enabling Autonomous Operation of Micro Aerial Vehicles Through GPS to GPS-Denied Transitions." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/8709.

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Micro aerial vehicles and other autonomous systems have the potential to truly transform life as we know it, however much of the potential of autonomous systems remains unrealized because reliable navigation is still an unsolved problem with significant challenges. This dissertation presents solutions to many aspects of autonomous navigation. First, it presents ROSflight, a software and hardware architure that allows for rapid prototyping and experimentation of autonomy algorithms on MAVs with lightweight, efficient flight control. Next, this dissertation presents improvments to the state-of-t

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18

Wieser, Andreas [Verfasser]. "GPS based velocity estimation : And its application to an odometer / Andreas Wieser." Aachen : Shaker, 2007. http://d-nb.info/1166512916/34.

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19

Wheeler, David Orton. "Relative Navigation of Micro Air Vehicles in GPS-Degraded Environments." BYU ScholarsArchive, 2017. https://scholarsarchive.byu.edu/etd/6609.

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Most micro air vehicles rely heavily on reliable GPS measurements for proper estimation and control, and therefore struggle in GPS-degraded environments. When GPS is not available, the global position and heading of the vehicle is unobservable. This dissertation establishes the theoretical and practical advantages of a relative navigation framework for MAV navigation in GPS-degraded environments. This dissertation explores how the consistency, accuracy, and stability of current navigation approaches degrade during prolonged GPS dropout and in the presence of heading uncertainty. Relative navig

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20

Hardt, Hans-Joachim von der. "Contribution au pilotage et à la localisation d'un robot mobile." Vandoeuvre-les-Nancy, INPL, 1997. http://www.theses.fr/1997INPL120N.

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Les travaux présentés dans ce mémoire traitent des problèmes relatifs au pilotage et à la localisation d'un robot mobile à roues. Le système de pilotage développé permet d'asservir un véhicule de type fauteuil roulant électrique sur des trajectoires de référence composées de segments rectilignes et de segments en forme de splines polaires. La localisation relative du robot mobile est assurée par un système multicapteur constitué de deux codeurs incrémentaux (odométrie), un gyromètre et un magnétomètre. Le calibrage étant primordial pour les performances du système multicapteur, une méthode d'a

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21

Diviš, Jiří. "Visual odometry from omnidirectional camera." Master's thesis, 2013. http://www.nusl.cz/ntk/nusl-328572.

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We present a system that estimates the motion of a robot relying solely on images from onboard omnidirectional camera (visual odometry). Compared to other visual odometry hardware, ours is unusual in utilizing high resolution, low frame-rate (1 to 3 Hz) omnidirectional camera mounted on a robot that is propelled using continuous tracks. We focus on high precision estimates in scenes, where objects are far away from the camera. This is achieved by utilizing omnidirectional camera that is able to stabilize the motion estimates between camera frames that are known to be ill-conditioned for narrow

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22

Diviš, Jiří. "Visual odometry from omnidirectional camera." Master's thesis, 2012. http://www.nusl.cz/ntk/nusl-305129.

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We present a system that estimates the motion of a robot relying solely on images from onboard omnidirectional camera (visual odometry). Compared to other visual odometry hardware, ours is unusual in utilizing high resolution, low frame-rate (1 to 3 Hz) omnidirectional camera mounted on a robot that is propelled using continuous tracks. We focus on high precision estimates in scenes, where objects are far away from the camera. This is achieved by utilizing omnidirectional camera that is able to stabilize the motion estimates between camera frames that are known to be ill-conditioned for narrow

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23

Zborovský, Peter. "Odhad hloubky ve scéně na základě obrazu a odometrie." Master's thesis, 2018. http://www.nusl.cz/ntk/nusl-383295.

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In this work, we propose a depth estimation system based on image sequence and odometry information. The key idea is that depth estimation is decoupled from pose estimation. Such approach results in multipurpose system applicable on different robot platforms and for different depth estimation related problems. Our implementation uses various filtration techniques, operates real-time and provides appropriate results. Although the system was aimed at and tested on drone platform, it can be well used on any other type of autonomous vehicle that provides odometry information and video output.

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24

Hong, Kai-Chen, and 洪楷宸. "The Study of Ego-motion Estimation for a Moving Object with Monocular Camera using Visual Odometry." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/x64wny.

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碩士<br>國立交通大學<br>電控工程研究所<br>107<br>Visual odometry is the process of estimating the ego-motion of a moving object. In other words, visual odometry is the process of determining the position of a moving object. Then, the SLAM system is considered to be the best method for spatial positioning technology in the visual field. However, the SLAM system is quite large (the front-end: visual odometry, the back-end: optimization of the ego-motion estimation error), If the system need to perform other arithmetic processing at the same time, it will face challenges in terms of real-time. There are two con

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25

Hänert, Stephan. "Entwicklung und Validierung methodischer Konzepte einer kamerabasierten Durchfahrtshöhenerkennung für Nutzfahrzeuge." 2019. https://tud.qucosa.de/id/qucosa%3A71402.

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Die vorliegende Arbeit beschäftigt sich mit der Konzeptionierung und Entwicklung eines neuartigen Fahrerassistenzsystems für Nutzfahrzeuge, welches die lichte Höhe von vor dem Fahrzeug befindlichen Hindernissen berechnet und über einen Abgleich mit der einstellbaren Fahrzeughöhe die Passierbarkeit bestimmt. Dabei werden die von einer Monokamera aufgenommenen Bildsequenzen genutzt, um durch indirekte und direkte Rekonstruktionsverfahren ein 3D-Abbild der Fahrumgebung zu erschaffen. Unter Hinzunahme einer Radodometrie-basierten Eigenbewegungsschätzung wird die erstellte 3D-Repräsentation skalier

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