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Articles 1 - 4 of 4
Full-Text Articles in Engineering
Integration Of Real-Time Semantic Building Map Updating With Adaptive Monte Carlo Localization (Amcl) For Robust Indoor Mobile Robot Localization, Matthew Peavy, Pileun Kim, Hafiz Oyediran, Kyungki Kim
Integration Of Real-Time Semantic Building Map Updating With Adaptive Monte Carlo Localization (Amcl) For Robust Indoor Mobile Robot Localization, Matthew Peavy, Pileun Kim, Hafiz Oyediran, Kyungki Kim
Durham School of Architectural Engineering and Construction: Faculty Publications
A robot can accurately localize itself and navigate in an indoor environment based on information about the operating environment, often called a world or a map. While typical maps describe structural layouts of buildings, the accuracy of localization is significantly affected by nonstructural building elements and common items, such as doors, appliances, and furniture. This study enhances the robustness and accuracy of indoor robot localization by dynamically updating the semantic building map with non-structural elements detected by sensors. We propose modified Adaptive Monte Carlo Localization (AMCL), integrating object recognition and map updating into the traditional probabilistic localization. With the proposed …
Automated Tree-Level Forest Quantification Using Airborne Lidar, Hamid Hamraz
Automated Tree-Level Forest Quantification Using Airborne Lidar, Hamid Hamraz
Theses and Dissertations--Computer Science
Traditional forest management relies on a small field sample and interpretation of aerial photography that not only are costly to execute but also yield inaccurate estimates of the entire forest in question. Airborne light detection and ranging (LiDAR) is a remote sensing technology that records point clouds representing the 3D structure of a forest canopy and the terrain underneath. We present a method for segmenting individual trees from the LiDAR point clouds without making prior assumptions about tree crown shapes and sizes. We then present a method that vertically stratifies the point cloud to an overstory and multiple understory tree …
An Obstacle Avoidance System For The Visually Impaired Using 3-D Point Cloud Processing, Evan Justin Taylor
An Obstacle Avoidance System For The Visually Impaired Using 3-D Point Cloud Processing, Evan Justin Taylor
Theses and Dissertations
The long white cane offers many benefits for the blind and visually impaired. Still, many report being injured both indoors and outdoors while using the long white cane. One frequent cause of injury is due to the fact that the long white cane cannot detect obstacles above the waist of the user. This thesis presents a system that attempts to augment the capabilities of the long white cane by sensing the environment around the user, creating a map of obstacles within the environment, and providing simple haptic feedback to the user. The proposed augmented cane system uses the Asus Xtion …
A Novel Dynamic Bandwidth Selection Method For Thinning Noisy Point Clouds, Mehmet Öztürk, Zeynep Hasirci
A Novel Dynamic Bandwidth Selection Method For Thinning Noisy Point Clouds, Mehmet Öztürk, Zeynep Hasirci
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose a dynamic bandwidth selection method for thinning noisy point clouds into curves. Due to the nonhomogeneous distribution of noise or varying curvature of the data, the thinning procedure requires a dynamically adjusted bandwidth along the curve. On the other hand, the selected local region must be sorted along a suitable direction vector for local curve fitting purposes. The contribution of this paper to the field is 2-folded: first, a normalized eigenvalue analysis-based method is used to determine the best local bandwidth. The second task is getting a good regression line of the local region for …