Computational analysis and design has become a fundamental part of product research, development, and manufacture in aerospace, automotive, and other industries. In general the success of the specific application depends heavily on the accuracy and consistency of the computational model used. The aim of this work is to reduce the time needed to prepare geometry for mesh generation. This will be accomplished by developing tools that semi-automatically repair discrete data. Providing a level of automation to the process of repairing large, complex problems in discrete data will significantly accelerate the grid generation process. The developed algorithms are meant to offer semi-automated solutions to complicated geometrical problems—specifically discrete mesh intersections and isolated boundaries. The intersection-repair strategy presented here focuses on repairing the intersection in-place as opposed to re-discretizing the intersecting geometries. Combining robust, efficient methods of detecting intersections and then repairing intersecting geometries in-place produces a significant improvement over techniques used in current literature. The result of this intersection process is a non-manifold, non-intersecting geometry that is free of duplicate and degenerate geometry. Results are presented showing the accuracy and consistency of the intersection repair tool. Isolated boundaries are a type of gap that current research does not address directly. They are defined by discrete boundary edges that are unable to be paired with nearby discrete boundary edges in order to fill the existing gap. In this research the method of repair seeks to fill the gap by extruding the isolated boundary along a defined vector so that it is topologically adjacent to a nearby surface. The outcome of the repair process is that the isolated boundaries no longer exist because the gap has been filled. Results are presented showing the precision of the edge projection and the advantage of edge splitting in the repair of isolated boundaries.

To handle broken 3D models can be a very time consuming problem. Several methods aiming for automatic mesh repair have been presented in the recent years. This thesis gives an extensive evaluation of automatic mesh repair algorithms, presents a mesh repair pipeline and describes an implemented automatic mesh repair algorithm. The presented pipeline for automatic mesh repair includes three main steps: octree generation, surface reconstruction and ray casting. Ray casting is for removal of hidden objects. The pipeline also includes a pre processing step for removal of intersecting triangles and a post processing step for error detection. The implemented algorithm presented in this thesis is a volumetric method for mesh repair. It generates an octree in which data from the input model is saved. Before creation of the output, the octree data will be patched to remove inconsistencies. The surface reconstruction is done with a method called Manifold Dual Contouring. First new vertices are created from the information saved in the octree. Then there is a possibility to cluster vertices together for decimation of the output. Thanks to a special Manifold criterion, the output is guaranteedto be manifold. Furthermore the output will have sharp and clear edges and corners thanks to the use of Singular Value Decomposition during determination of the positions of the new vertices.

Current Augmented Reality devices rely heavily on real-time environment mapping to provide convincing world-relative experiences through user interaction with virtual content integrated into the real world. This mapping is obtained and updated through many different algorithms, but often results in holes and other mesh artifacts when generated in less ideal scenarios, like outdoors and with fast movement. In this work, we present the Interaction-Triggered Estimation of AR Object Placement on Indeterminate Meshes, a quick, interaction-triggered method to estimate the normal and position of missing mesh pieces in real-time with low computational overhead. We achieve this by extending the user's hand using a group of additional raycast sample points, aggregating results according to different algorithms, and then using the resulting values to place an object. This thesis will first cover problems with current mapping techniques, thoroughly explain the rationale and algorithms behind our method, and then evaluate our method using a user study. / Master of Science / Augmented Reality (AR) technologies have the potential to change all our lives for the better through tight and seamless integration into our daily lives. Crucial to this seamless integration is the ability for users to manipulate virtual AR objects and interact effortlessly with real-world features around them. In order to facilitate this interaction, AR devices often create 3D maps of the real world to allow the device to recognize and respect the geometry of the world around it. Unfortunately, many AR devices still have trouble creating and maintaining these maps in challenging environments, like outdoors or when moving fast, so the resulting 3D maps of the environments have holes and inaccuracies, causing user interaction with the environment to be unreliable and breaking the seamless integration. While many solutions look toward more advanced algorithms that require more specialized sensors or next-gen AR devices to improve this mapping issue, we see an opportunity to enhance any existing 3D maps using a novel interaction aggregation approach that can theoretically work with any mapping technology. In this work, we present the Interaction-Triggered Estimation of AR Object Placement on Indeterminate Meshes, a work-in-progress application providing a quick, interaction-triggered method to estimate the normal and position of missing mesh in real-time with low computational overhead.

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