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 130 for “"Simultaneous localization and mapping"”.
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Underwater Semantic Simultaneous Localization and Mapping
… autonomy, fostering human-robot collaboration, and providing compressed map representations for bandwidth-constrained underwater communications, while localizing against such maps can improve the positioning accuracy of underwater vehicles by correcting for odometric drift. However, underwater …
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Robust non-Gaussian semantic simultaneous localization and mapping
… for robot navigation; i.e. semantic simultaneous localization and mapping (SLAM), in which we aim to jointly estimate the pose of the robot over time as well as the location and semantic class of observed objects. A solution to the semantic SLAM problem necessarily addresses the …
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Robust non-Gaussian semantic simultaneous localization and mapping
… for robot navigation; i.e. semantic simultaneous localization and mapping (SLAM), in which we aim to jointly estimate the pose of the robot over time as well as the location and semantic class observed objects. A solution to the semantic SLAM problem necessarily addresses the …
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Using Negative Information in simultaneous localization and mapping
… utilizing available information from sensors and intelligently processing that information to determine the state of the robot and its environment. This thesis explores a topic often ignored in the Simultaneous Localization And Mapping (SLAM) literature: the utility of including Negative …
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A simultaneous localization and mapping implementation using inexpensive hardware
… the past few decades, influencing both industry and academia. The strategy of making robots navigate autonomously adds many problems however. Many of these problems are directly related to the robot's ability to localize and autonomously map its environment. A solution to this problem is called …
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Efficient simultaneous localization and mapping algorithms using submap networks
Autonomous mapping of large-scale environments has been a critical challenge confronting researchers in mobile robotics. This thesis investigates two aspects of the large-scale simultaneous localization and mapping (SLAM) problem: (1) the behavior of the covariance matrix in the Kalman filter …
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Visual Simultaneous Localization and Mapping: From Geometry to Deep Learning
Visual Simultaneous Localization and Mapping (SLAM) is essential to achieve persistent autonomy for mobile robots in unknown environments, and is a key technique for enormous vision based applications, such as virtual and augmented reality. Researchers from the robotics and computer vision …
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Real-time dense simultaneous localization and mapping using monocular cameras
… etc.), while being lightweight, low-power, and inexpensive. Exploiting such sensor data for navigation tasks typically falls into the realm of monocular simultaneous localization and mapping (SLAM), where both the robot's pose and a map of the environment are estimated concurrently from the …
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Active Simultaneous Localization and Mapping in Perceptually Aliased Underwater Environments
The problem of semantic simultaneous localization and mapping (SLAM) is especially difficult in underwater environments due to sensor characteristics and terrain. The primary underwater sensor, sonar, is subject to multipath reflections, as well as an elevation angle ambiguity that makes it …
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A comparison of data association techniques for Simultaneous Localization and Mapping
The problem of Simultaneous Localization and Mapping (SLAM) has received a great deal of attention within the robotics literature, and the importance of the solutions to this problem has been well documented for successful operation of autonomous agents in a number of environments. Of the numerous …
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Towards a Visual Simultaneous Localization and Mapping System for Computationally Constrained Systems
… exploration missions such as sample retrieval and in-situ resource utilization will require more accurate localization techniques such as Simultaneous Localization and Mapping (SLAM) to achieve the science goals. In this thesis, a visual SLAM system aimed towards computationally constrained …
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Introspective learning based Visual-LiDAR fusion for adaptive Simultaneous Localization and Mapping
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms
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Towards a Fast, Robust and Accurate Visual-Inertial Simultaneous Localization and Mapping System
A Simultaneous Localization and Mapping (SLAM) system estimates a robot's instantaneous location using onboard sensory measurements, e.g., LiDAR (Light Detection and Ranging) sensors, cameras, and inertial measurement units (IMU). It is particularly challenging where GPS reception is weak such as …
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Active perception in visual simultaneous localization and mapping by feature / map point selection
Made available in DSpace on 2020-03-02T22:15:17Z (GMT). No. of bitstreams: 3 SHANGGUAN-THESIS-2019.pdf: 2228824 bytes, checksum: 5b85d2af527e7f9f5ccd86676233811f (MD5) ZhengheShangguan_Thesis-Master.docx: 3626082 bytes, checksum: d163037c82f5c7bd6cd1d7b6167c7684 (MD5) LICENSE.txt: 4214 bytes, …
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Recovering sample diversity in Rao-Blackwellized particle filters for simultaneous localization and mapping
… the Rao-Blackwellized particle filter (RBPF) in simultaneous localization and mapping (SLAMI) situations that arises when precise feature measurements yield a limited perceptual distribution relative to a motion-based proposal distribution. One set of solutions propagates particles according to a …
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Indoor 3D Modeling Using Consumer Drones and Neural Simultaneous Localization and Mapping (SLAM) for Virtual Reality
This thesis explores an accessible indoor mapping system utilizing consumer-grade drones, addressing inefficiencies in traditional indoor spatial capture methods. The research demonstrates high-quality mapping accuracy with consumer hardware, creates a modular architecture for simplified operation, …
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An Experimental Evaluation of Learning-Based Methods for Loop Closure Detection in Simultaneous Localization and Mapping
Simultaneous Localization and Mapping (SLAM) is the capability to estimate a robot’s trajectory in an initially unknown environment while reconstructing the geometry of the environment. In order to bound the accumulation of localization error in SLAM, it is crucial to recognize previously seen …
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Design of an autonomous underwater vehicle to evaluate the blazed array sonar and simultaneous localization and mapping algorithms
… design of the overall vehicle, (2) specification and acquisition of the electronic components of the vehicle, including its main CPU, and (3) mechanical design of selected components, including the ship's hull, servo-controlled fin system, and blazed array sonar nose cone. These contributions have …
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On the utilization of Simultaneous Localization and Mapping(SLAM) along with vehicle dynamics in Mobile Road Mapping Systems
Mobile Road Mapping Systems (MRMS) are the current solution to the growing demand for high definition road surface maps in wide ranging applications from pavement management to autonomous vehicle testing. The focus of this research work is to improve the accuracy of MRMS by using the principles of …
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Semantic and Fiducial Aided Graph Simultaneous Localization and Mapping for Robotic In-Space Assembly and Servicing of Large Truss Structures
… focuses on the development of the semantic and fiducial aided graph simultaneous localization and mapping (SF-GraphSLAM) method that is tailored for robotic assembly and servicing of large truss structures. SF-GraphSLAM contributes to the state of the art by creating a novel way to add …
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