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 13 of 13 for “"SEMANTIC MAP"”.
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Using 3D Visual Data to Build a Semantic Map for Autonomous Localization
Environment maps are essential for robots and intelligent gadgets to autonomously carry out tasks. Traditional maps built by visual sensors include metric ones and topological ones. These maps are navigation-oriented and not adequate for service robots or intelligent gadgets to interact with or …
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BIO-INSPIRED DESIGN METHODOLOGY BASED ON A SEMANTIC MAP, USEABLE IN CAD ENVIRONMENT
… couples of analogies has been used to build a semantic mapping. This allows for enhanced integration with CAD and therefore in the complex product lifecycle management systems. In this way the information becomes more accessible, it can be modified, shared and used by all those involved in the …
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The semantic map of verbal troponymy and aktionsart of old English lexical paradigms based on strong verbs
… El análisis aplica la metodología de los mapas semánticos y se centra en dos características intrínsecas de los verbos: la troponimia y el Aktionsart. El objetivo de esta tesis doctoral es obtener un mapa semántico dual de los paradigmas léxicos de los verbos fuertes de inglés antiguo. Los …
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Solving the Traveling Salesman Problem via Semantic Segmentation with Convolutional Neural Networks
… Heuristic (HIH) that converts a road network semantic map into a truncated distance matrix that can be passed to a traditional TSP solution algorithm. The HIH can be further augmented in the image domain with our proposed novel Convolutional Neural Network (CNN). Our proposed CNN takes as …
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Learning to understand spatial language for robotic navigation and mobile manipulation
… object is likely to be found. The system uses a semantic map of the environment together with a model of contextual relationships between objects to infer this plan, which finds the query object with minimal travel time. The contextual relationships are learned from the captions of a large …
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Semantic Mapping of Road Scenes
… First, we propose a solution to generate a dense semantic map from multiple street-level images. This map can be imagined as the bird’s eye view of the region with associated semantic labels for ten’s of kilometres of street level data. We generate the overhead semantic view from street level …
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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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Learning 3D Robotics Perception using Inductive Priors
… priors from synthetic data, 2. modularity and semantic map priors and 3. semantic, structural, and contextual priors. I study these priors for solving robotics 3D perception tasks and propose ways to efficiently encode them in deep learning models. Some priors are used to warm-start the network …
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3D Spatial Perception with Real-Time Dense Metric-Semantic SLAM
… this thesis first proposes the use of a map representation that is geometrically dense, photometrically accurate, and semantically annotated. We define these maps as metric-semantic maps, and provide algorithms to build such maps in real-time. Metric-semantic maps allow both humans and …
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Multimodal Concept Detection and Annotation in Image and Video Collections
… In order to retrieve relevant information, the semantic relationships of the information in different modalities would need to be known and specified. This thesis approaches the multimodal cross-domain semantic retrieval and fusion problem from the point of view of content-based visual analysis …
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Learning Birds-Eye View Representations for Autonomous Driving
… as well the use of detailed high-resolution maps, which together allow a vehicle to navigate its surroundings effectively. Often, however, one or both of these resources may be unavailable, whether due to cost, sensor failure, or the need to operate in an unmapped environment. The aim of this …
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Semantic and Fiducial Aided Graph Simultaneous Localization and Mapping for Robotic In-Space Assembly and Servicing of Large Truss Structures
This research 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 …
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Learning semantic maps from natural language
… Current approaches to constructing such spatial-semantic representations rely solely on traditional sensors to acquire knowledge of the environment, which restricts robots to learning limited knowledge of their local surround. Furthermore, they can only reason over the limited portion of the …