Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 74 for “"odometry"”.
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MONOCULAR VISUAL ODOMETRY
… visual input alone using methods such as visual odometry (VO) or visual simultaneous localization and mapping (V-SLAM), motion can only be recovered only up to an unknown scale factor in a monocular setup. Visual place recognition (VPR) can provide absolute pose estimates by matching the current …
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Fusing visual odometry and depth completion
… with triangulations from a typical sparse visual odometry pipeline. We are then able to achieve a small improvement over the single image baseline and chart guidelines to assist in designing a system with even more substantial gains.
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Visual Inertial Odometry with Sparse Deep Learning
… essential to localizing a robot. Visual Inertial Odometry (VIO) systems try to figure out the position and orientation of a robot by analyzing data from cameras and inertial sensors. As state-of-the-art VIO systems achieve remarkable accuracy, there are still improvements to be made in terms of …
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Monocular Visual Inertial Odometry using Learning-based Methods
… sensor or multiple sensors. Visual Inertial Odometry (VIO) uses images and inertial measurements to estimate the motion and is considered a key technology for GPS-denied localization in the real world and also virtual reality and augmented reality.</p> <p>This study develops three novel …
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Learning visual odometry primitives for computationally constrained platforms
… (SWAP) budget robots. Unlike for traditional odometry methods, in this case, a machine learning model can be trained offline, and can then generate odometry measurements quickly and efficiently. This thesis describes the implementation of the learning-based, visual odometry method in the …
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Loosely coupled LiDAR-Visual/Thermal-Inertial Odometry and Mapping
… a loosely coupled LiDAR-Visual/Thermal-Inertial odometry and mapping method that uses factor graphs. Our approach jointly optimizes relative pose constraints provided by a LiDAR scan-to-scan alignment method and a Visual/Thermal-Inertial method with preintegrated IMU constraints. An optimized …
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Planar Motion and Visual Odometry: Pose Estimation from Homographies
This thesis concerns ego-motion and pose estimation of a single camera under the assumptions of planar motion and constant internal camera parameters. Planar motion is common for cameras mounted onto mobile robots, particularly in indoor scenarios, as they remain at a constant height above the …
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Direct Visual and Inertial Odometry for Monocular Mobile Platforms
… are explored in details. Two visual-inertial odometry algorithms are proposed in the framework of multi-state constraint Kalman filter. They are also tested with the real data from a flying robot in complex indoor and outdoor environments. The results show that the direct-based methods have …
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Deep Reinforcement Learning for Robotic Tasks: Manipulation and Sensor Odometry
… accuracy of these vehicles. Recent sensor odometry research suggests that Lidar Monocular Visual Odometry (LIMO) can be beneficial for determining odometry. However, the LIMO algorithm has a considerable number of errors when compared to ground truth, which motivates us to investigate ways …
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Sparsity and computation reduction for high-rate visual-inertial odometry
The navigation problem for mobile robots operating in unknown environments can be posed as a subset of Simultaneous Localization and Mapping (SLAM). For computationally-constrained systems, maintaining and promoting system sparsity is key to achieving the high-rate solutions required for agile …
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Visual-inertial odometry with depth sensing using a multi-state constraint Kalman filter
The goal of visual inertial odometry (VIO) is to estimate a moving vehicle's trajectory using inertial measurements and observations, obtained by a camera, of naturally occurring point features. One existing VIO estimation algorithm for use with a monocular system, is the multi-state constraint …
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Evaluating UAV Visual-Inertial Odometry Trajectory Error and Feature-Level Metrics over Repetitive Floor Patterns
<p>Visual-Inertial Odometry (VIO) is a widely used state estimation technique for Uncrewed Aerial Vehicle (UAV) navigation in environments where Global Navigation Satellite System (GNSS) signals are unavailable. VIO systems that rely on visual feature tracking are susceptible to performance …
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Improved pose estimation accuracy of monocular deep visual odometry against dynamic entities via adversarial training
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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Development and evaluation of a dynamically scaled testbed aircraft for a visual inertial odometry dataset
… (DEP) aircraft research and for Visual Inertial Odometry (VIO) research. The aircraft is used as a baseline to compare with the DEP aircraft, to draw conclusion regarding the effect of changing to a DEP configuration, and to provide a way to measure the effect that a DEP configuration would have …
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TECHNOLOGICAL BREAKTHROUGH TOWARDS THE USE OF A NOVEL VISUAL-INERTIAL ODOMETRY SYSTEM AS AN AID FOR THE DIGITALLY-GUIDED INTERVENTION
Recent data availability of three dimensional imaging brought new possibilities for the guided intervention. The management of complex data requires the use of new tools and new technologies. We analyzed the use of algorithms for the automatic, ai-driven segmentation to extrapolate the best systems …
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Enhancing Body-Mounted LiDAR SLAM using an IMU-based Pedestrian Dead Reckoning (PDR) Model
… mainly for robotic platforms that use wheel odometry. However, wheel odometry is not available for body-mounted platforms. This thesis addresses the challenge of body-mounted SLAM by proposing an integrated sensor fusion scheme. A Pedestrian Dead Reckoning (PDR) model based on inertial …
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Self-Supervised Learning for Geometry
… depth estimation (mapping) and two view visual odometry (tracking) and propose a self-supervised framework, namely SelfTAM, which jointly learns the depth estimator and the odometry estimator. The self-supervised problem is usually formulated as an energy minimization problem consist of an …
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Visual-Inertial State Estimation With Information Deficiency
… first step to image rendering. Visual-inertial odometry (VIO) is the de-facto standard algorithm for embedded platforms because it lends itself to lightweight sensors and processors, and maturity in research and industrial development. Various approaches have been proposed to achieve accurate …
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State estimation for a holonomic omniwheel robot using a particle filter
… developed to control robot vectoring and report odometry, and noise analysis on an absolute positioning system, Ubisense, was performed to characterize the system. High frequency noise confounds the Ubisense measurement of 0, but the Particle Filter acts as a low pass filter on the absolute …
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