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 18 of 18 for “"Object Pose Estimation"”.
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Robotic object pose estimation with deep neural networks
In this work, we introduce pose interpreter networks for 6-DoF object pose estimation. In contrast to other CNN-based approaches to pose estimation that require expensively-annotated object pose data, our pose interpreter network is trained entirely on synthetic data. We use object masks as an …
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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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Robust object pose estimation with point clouds from vision and touch
We present a study of object pose estimation performed with hybrid visuo-tactile sensing in mind. We propose that a tactile sensor can be treated as a source of dense local geometric information, and hence consider it to be a point cloud source analogous to an RGB-D camera. We incorporate the …
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Active Multi-View Object Pose Estimation Using a Mobile Ground Robot
Accurate 6-DoF object pose estimation remains a central challenge in robotic perception, particularly when relying on single-view observations subject to occlusions and limited geometric cues. This thesis presents a system that incrementally refines object pose estimates by collecting multi-view …
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Advancing 6DoF Object Pose Estimation: Keypoint Voting, Optimal Keypoint Sampling, and Bridging the Simulation-to-real Gap
… advancements in six-degree-of-freedom (6DoF) object pose estimation using point cloud and RGB-D data. Three novel methodologies are proposed to address distinct challenges in this field. First, RCVPose3D introduces a cascaded keypoint voting framework that separates semantic segmentation from …
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VISION-BASED ROBOTIC MANIPULATION
… of vision-based robotic manipulation: Grasp Pose Estimation, Object Pose Estimation, and Affordance Estimation, aiming to enhance the precision and adaptability of robotic systems in unstructured environments.
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Uncertainty Quantification in the context of 6D Pose Estimation
… 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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Towards Self-Supervised Object Representations and 3D Scene Graph Based Navigation
… the art in dense 2D semantic segmentation and 3D object pose estimation to improve scene graph construction and enable navigation in real-life environments. First, we tackle the scalability problem of data annotation for deep semantic segmentation and introduce a simple training approach for dense …
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Learning articulated motions from visual demonstration
… must be capable of interacting with articulated objects on a daily basis. They should be able to infer each object's underlying kinematic linkages purely by observing its motion during manipulation. This work proposes a framework that enables robots to learn the articulation in objects from …
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RGB-D Likelihood for 3D Inverse Graphics
… between 3D graphics and real-world data. We propose a novel 3D Neural Embedding Likelihood (3DNEL) over RGB-D images to address this gap. 3DNEL uses neural embeddings to predict 2D-3D correspondences from RGB and combines this with depth in a principled manner. 3DNEL is trained entirely from …
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Deep learning-based approaches for depth and 6-DoF pose estimation
… geometric vision problems, namely, depth estimation from a single RGB image, and 6-DoF object pose estimation from a partial point cloud. Geometric vision problems are concerned with extracting information (e.g. depth, agent trajectory, 3D structure, 6-DoF pose of objects) of the scene …
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Reconfigurable Autonomous Surface Vehicles : perception and trajectory optimization algorithms
… enable robust and precise obstacle avoidance and object pose estimation on the water. Additionally, operating ASVs in well-networked urban waterways creates many potential use cases for ASVs to serve as re-configurable urban infrastructure, but this necessitates developing novel multi-robot …
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Geometrically and Temporally Consistent Robot Perception
… to reconcile an ideal mathematical model of an object with imperfect data. Despite having been investigated extensively, robot perception remains challenging with spurious outliers, limited training data, and computational constraints. To this end, we investigate geometric and temporal …
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Graph-Theoretic Outlier Rejection: From Instance to Category-Level Perception
… study the problem of outlier pruning for robust estimation. Robust estimation is the workhorse for many perception problems, from object pose estimation to robot localization and mapping. In these problems, the robot has to estimate quantities of interest in the face of outliers. Such outliers …
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Towards Active Object-Based Navigation
… the design and implementation of an active object-based navigation system. Localization refers to the capability of a mobile robot to determine its position relative to a prior map of the environment. Localization based on fiducial markers, such as AprilTags, has been a popular technique …
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Developing a mobile manipulation system to handle unknown and unstructured objects
… human’s ability to interact with unknown objects based on minimal prior experience is a permanent inspiration to the field of robotic manipulation. The recent revolution in industrial and service robots demands high-autonomy and intelligent mobile-manipulators. The goal of the thesis is to …
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Toward visual understanding of everyday object
… vision community has made impressive progress on object recognition using large scale data. However, for any visual system to interact with objects, it needs to understand much more than simply recognizing where the objects are. The goal of my research is to explore and solve object understanding …