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 145 for “"Localization And Mapping"”.
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Toward lifelong visual localization and mapping
… durations require algorithms that are robust and scale efficiently over time as sensor information is continually collected. For mobile robots one of the fundamental problems is navigation; which requires the robot to have a map of its environment, so it can plan its path and execute it. …
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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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Toward lifelong visual localization and mapping
… durations require algorithms that are robust and scale efficiently over time as sensor information is continually collected. For mobile robots one of the fundamental problems is navigation; which requires the robot to have a map of its environment, so it can plan its path and execute it. …
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Sparse Bayesian information filters for localization and mapping
… an estimation framework for Simultaneous Localization and Mapping (SLAM) that addresses the problem of scalability in large environments. We describe an estimation-theoretic algorithm that achieves significant gains in computational efficiency while maintaining consistent estimates for 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 of observed objects. A solution to the semantic SLAM problem necessarily addresses the continuous …
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Measurement consensus metric aided lidar localization and mapping
In LiDAR Simultaneous Localization and Mapping (SLAM), probability distribution approximations of point clouds, such as the Normal Distribution Transform (NDT), can be leveraged for compact map storage and fast lookup. Augmentation of these techniques with a measurement consensus-based estimate of …
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Sparse Bayesian information filters for localization and mapping
… an estimation framework for Simultaneous Localization and Mapping (SLAM) that addresses the problem of scalability in large environments. We describe an estimation-theoretic algorithm that achieves significant gains in computational efficiency while maintaining consistent estimates for 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 continuous inference …
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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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Vision based estimation, localization, and mapping for autonomous vehicles
… we focus on developing simultaneous localization and mapping (SLAM) algorithms with a robot-centric estimation framework primarily using monocular vision sensors. A primary contribution of this work is to use a robot-centric mapping framework concurrently with a world-centric …
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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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Applications of Sensor Fusion to Classification, Localization and Mapping
… Networks (WSN), the Internet of Things (IoT), and spectrum sharing schemes, depend on large numbers of distributed nodes working collaboratively and sharing information. In addition, there is a huge proliferation of smartphones in the world with a growing set of cheap powerful embedded sensors. …
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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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Localization and Mapping for Autonomous Driving: Fault Detection and Reliability Analysis
… has advanced rapidly during the past decades and has expanded its application for multiple fields, both indoor and outdoor. One of the significant issues associated with a highly automated vehicle (HAV) is how to increase the safety level. A key requirement to ensure the safety of automated …
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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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Localization And Mapping Of Unknown Locations And Tunnels With Unmanned Ground Vehicles
… the platform within a simulation environment, and to validate the architecture through field testing. Developing this platform will enhance the U. S. Army Engineering Research and Development Center’s (ERDC’s) current capabilities and create a safe and efficient autonomous vehicle to perform …
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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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