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 7 of 7 for “"6D pose estimation"”.
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Uncertainty Quantification in the context of 6D Pose Estimation
… use the Deep Evidential method in the context of 6D Object Pose Estimation, where it can be crucial to have both information on the prediction and the uncertainty on the prediction (really important for safety-critical robotic manipulation).
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3D Deep Learning for Object-Centric Geometric Perception
… of 3D objects. These attributes include shape, pose, and motion of the target objects, which enable fine-grained object-level understanding for various tasks in graphics, computer vision, and robotics. With the growth of 3D geometry data and 3D deep learning methods, it becomes more and more …
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Neural Representation for robotics
… subtasks: geometry reconstruction, pose estimation, and grasp prediction. Geometry reconstruction has conventionally relied on depth cameras. However, these cameras are susceptible to numerous limitations, including occlusions, reflections, challenging lighting conditions, and …
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A Collaborative Industrial Robotic System with Machine-Learned Trajectory Planning and Control
… works with industrial robots is proposed, which combines the high precision, repeatability and strength of robots with the flexibility and adaptability of human workers. This thesis presents a system implementation for collaborative industrial robots that addresses critical gaps in …
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Vision-based 6D object pose estimation for robot manipulation
Vision-based 6D object pose estimation focuses on estimating the 3D translation and 3D orientation of an object with respect to the camera. Accurately estimating the 6D object pose plays a crucial role in various robotic applications such as robot manipulation and semantic navigation. In this …
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A fast selective grasping algorithm with deep learning and autonomous dataset creation on point cloud
… of depth and geometry than RGB images. The proposed algorithm leverages geometric primitive estimation and lateral curvatures to identify optimal grasping regions swiftly and efficiently, where only the object geometry is used to analyze where to grasp. To ensure the selection of desirable …
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Learning 3D Robotics Perception using Inductive Priors
… To solve these challenging problems, I propose various sources of prior knowledge including 1. geometry and appearance 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 …