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 240 for “"SLAM"”.
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Certifiably correct SLAM
… problem, simultaneous localization and mapping (SLAM), is typically formulated as a maximum-likelihood estimation (MLE) that requires solving a nonconvex nonlinear program, which is computationally hard. Current state-of-the-art SLAM algorithms address this difficulty by applying fast local …
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Visual-inertial curve SLAM
… present a simultaneous localization and mapping (SLAM) algorithm that uses B\'{e}zier curves as static landmark primitives rather than feature points. Our approach allows us to estimate the full 6-DOF pose of a robot while providing a sparse structured map which can be used to assist a robot in …
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Analytical SLAM without linearization
… of simultaneous localization and mapping (SLAM) in a fashion which avoids linearized approximations altogether. Based on creating virtual synthetic measurements, the algorithm uses a linear time-varying (LTV) Kalman observer, bypassing errors and approximations brought by the linearization …
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Towards Object-based SLAM
Simultaneous localization and mapping (SLAM) is a fundamental capability for a robot to perceive its surrounding environment. The research area has developed for more than two decades from the original sparse landmark-based SLAM to dense SLAM, and now there is a demand for semantic understanding of …
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Integrating SLAM-DUNK and variable rate particle observers for fast multi-hypothesis SLAM
In this thesis, the problem of SLAM with some set of prior hypotheses about the map, called Multi-Hypothesis SLAM, was tackled using a combination of an existing landmark-based SLAM algorithm called SLAM-DUNK and a particle filter inspired approach. SLAM-DUNK is a recent Kalman Filter-based …
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Towards Observable Urban Visual SLAM
Visual Simultaneous Localisation and Mapping (V-SLAM) is the subject of robot state and environment map estimation by drawing inference on camera captured data. It has been a major branch of research and popular in application owing to the rich information and low cost in vision measurement …
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Prioritized text spotting using SLAM
… We use simultaneous localization and mapping (SLAM) to isolate planar "tiles" representing scene surfaces and prioritize each tile according to its distance and obliquity with respect to the sensor, and how recently (if ever) and at what scale the tile has been inspected for text. We can also …
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Graphical SLAM for urban UAV navigation
… apply a Simultaneous Localization and Mapping (SLAM) approach to fuse GPS pseudorange measurements with LiDAR point clouds and 3D building footprint data of the existing region, for UAV trajectory estimation and environment mapping. Our approach consists of three main aspects: graphical …
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Experimental Evaluation of Underwater Semantic SLAM
… semantic Simultaneous Localization and Mapping (SLAM) system for underwater environments, implemented on the cost-effective BlueROV2 platform. The research aims to enhance AUV autonomy and enable complex underwater missions through improved navigation and semantic mapping capabilities. Key …
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ORB-based SLAM accelerator on SoC FPGA
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01
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V-SLAM and Sensor Fusion for Ground Robots
… its surroundings. This is the main reason why SLAM gained the popularity it has today. In recent years, we have seen excellent improvement on accuracy of localization using cameras and combinations of different sensors, especially camera-IMU (VIO) fusion. Incorporating more sensors leads to …
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Technologie SLAM při pasportizaci budov pomocí laserového skenování
… metodou laserového skenování technologií SLAM. Práce byla zaměřena na prostředí sběru dat pro tvorbu výkresové dokumentace pasportizace budov. Referenční metodou pro účely posouzení výsledků získaných SLAM technologií se stalo statické laserové skenování, Kvalita referenční technologie …
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SLAM-aware, self-supervised perception in mobile robots
Simultaneous Localization and Mapping (SLAM) is a fundamental capability in mobile robots, and has been typically considered in the context of aiding mapping and navigation tasks. In this thesis, we advocate for the use of SLAM as a supervisory signal to further the perceptual capabilities in …
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Software and Hardware Infrastructure for Visual-Inertial SLAM
… Simultaneous Localization and Mapping (SLAM) systems. SLAM is a fundamental problem in robot navigation and enables constructing or updating a representation (map) of an environment utilizing sensors on board a robot while concurrently using that representation to localize the robot …
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Toward robust active semantic SLAM via Max-Mixtures
In a step towards the level of autonomy seen in humans, this work attempts to emulate a high level and low level approach to world representation and short term adaptation. Specifically, this work demonstrates an implementation of robotic perception that transforms stereo camera and LIDAR sensor …
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SLAM for structured environments using mechanically scanned imaging sonar
… Simultaneous Localization and Mapping (SLAM) through acoustic means utilizing a Mechanically Scanned Imaging Sonar (MSIS). MSIS utilize a single beam sonar mechanically rotated around the vehicle to scan a full 360◦ area. Compared with other sonar systems of similar capabilities, they …
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Identifizierung von SLAM (CD150) als zellulären Rezeptor für Masernviren
… als signaling lymphocytic activation molecule (SLAM; CD150) identifiziert werden. Zur Untersuchung der Rezeptorbenutzung verschiedener MV-Stämme wurden CHO-Zellen, die entwe-der rekombinantes CD46 oder SLAM exprimierten, mit 28 Masernvirusstämmen infiziert. Unter den getesteten Viren befanden …
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Multiple Mobile Robot SLAM for collaborative mapping and exploration
… the map. Simultaneous Localisation and Mapping (SLAM) address the problem of both map building and robot localisation. When exploring large areas, Multi-Robot SLAM (MRSLAM) has the potential to be far more efficient and robust, while sharing the computational burden across robots. However, MRSLAM …
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