PHYSICS-AWARE MODEL SIMPLIFICATION FOR INTERACTIVE VIRTUAL ENVIRONMENTS

Rigid body simulation is an integral part of Virtual Environments (VE) for autonomous planning, training, and design tasks. The underlying physics-based simulation of VE must be accurate and computationally fast enough for the intended application, which unfortunately are conflicting requirements. Two ways to perform fast and high fidelity physics-based simulation are: (1) model simplification, and (2) parallel computation. Model simplification can be used to allow simulation at an interactive rate while introducing an acceptable level of error. Currently, manual model simplification is the most common way of performing simulation speedup but it is time consuming. Hence, in order to reduce the development time of VEs, automated model simplification is needed. The dissertation presents an automated model simplification approach based on geometric reasoning, spatial decomposition, and temporal coherence. Geometric reasoning is used to develop an accessibility based algorithm for removing portions of geometric models that do not play any role in rigid body to rigid body interaction simulation. Removing such inaccessible portions of the interacting rigid body models has no influence on the simulation accuracy but reduces computation time significantly. Spatial decomposition is used to develop a clustering algorithm that reduces the number of fluid pressure computations resulting in significant speedup of rigid body and fluid interaction simulation. Temporal coherence algorithm reuses the computed force values from rigid body to fluid interaction based on the coherence of fluid surrounding the rigid body. The simulations are further sped up by performing computing on graphics processing unit (GPU). The dissertation also presents the issues pertaining to the development of parallel algorithms for rigid body simulations both on multi-core processors and GPU. The developed algorithms have enabled real-time, high fidelity, six degrees of freedom, and time domain simulation of unmanned sea surface vehicles (USSV) and can be used for autonomous motion planning, tele-operation, and learning from demonstration applications

Brain Tumour Classification Using Deep Features from Structural MRI

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Multilinear motion synthesis with level-of-detail controls

Interactive animation systems often use a level-of-detail(LOD) control to reduce the computational cost by eliminatingunperceivable details of the scene. Most methodsemploy a multiresolutional representation of animationand geometrical data, and adaptively change the accuracylevel according to the importance of each character.Multilinear analysis provides the efficient representation ofmultidimensional and multimodal data, including humanmotion data, based on statistical data correlations. Thispaper proposes a LOD control method of motion synthesiswith a multilinear model. Our method first extracts asmall number of principal components of motion samplesby analyzing three-mode correlations among joints, time,and samples using high-order singular value decomposition.A new motion is synthesized by interpolatingthe reduced components using geostatistics, where theprediction accuracy of the resulting motion is controlledby adaptively decreasing the data dimensionality. Weintroduce a hybrid algorithm to optimize the reductionsize and computational time according to the distancefrom the camera while maintaining visual quality. Ourmethod provides a practical tool for creating an interactiveanimation of many characters while ensuring accurate andflexible controls at a modest level of computational cost

Virtual reality for assembly methods prototyping: a review

Assembly planning and evaluation is an important component of the product design process in which details about how parts of a new product will be put together are formalized. A well designed assembly process should take into account various factors such as optimum assembly time and sequence, tooling and fixture requirements, ergonomics, operator safety, and accessibility, among others. Existing computer-based tools to support virtual assembly either concentrate solely on representation of the geometry of parts and fixtures and evaluation of clearances and tolerances or use simulated human mannequins to approximate human interaction in the assembly process. Virtual reality technology has the potential to support integration of natural human motions into the computer aided assembly planning environment (Ritchie et al. in Proc I MECH E Part B J Eng 213(5):461–474, 1999). This would allow evaluations of an assembler’s ability to manipulate and assemble parts and result in reduced time and cost for product design. This paper provides a review of the research in virtual assembly and categorizes the different approaches. Finally, critical requirements and directions for future research are presented

Scanned surface to CAD design: matching, alignment and difference evaluation

This work proposes a tool to compare a high-precision surface scan with its original CAD model. The project is divided into three steps: how to process the CAD files, compute and optimize the registration, and develop tools for visualization. Because CAD files can contain multiple representations, we can't work directly with them. Normally this is approached by triangulating the described components and simplifying the mesh for a fast rendering, but this doesn't work for our high-density scans. Instead, we need to process the CAD to obtain a point cloud with a parameterized distance between points ---this will give a good starting point for the registration---. Next, the registration can be divided into two parts, coarse and fine. For the coarse register, we adapt the Initial Alignment Sample Consensus algorithm (IA RanSac) to automate the configuration settings and optimize the time for our input size. While in the fine register we will use the classic Iterative Closest Point (ICP). Due to the approach being a random consensus and the input being two big points cloud, reducing the number of points to a feasible number (statistically and computationally) will be essential to find a solution. For this, we developed a local optimizer that combines a set of LOD to find a global solution. Finally, to analyze the result, we have developed a color visualization interface with a set of modifier tools (colormaps, transparencies, range modifiers, etc.). This allows us to detect discrepancies between the two models that can be caused by wear or manufacturing imperfections

Statistical and Directable Methods for Large-Scale Rigid Body Simulation

This dissertation describes several techniques to improve performance and controllability of large-scale rigid body simulations. We first describe a statistical simulation method that replaces certain stages of rigid body simulation with a statistically- based approximation. We begin by collecting statistical data regarding changes in linear and angular momentum for collisions of a given object. From the data, we extract a statistical ”signature” for the object, giving a compact representation of the object’s response to collision events. During object simulation, both the collision detection and the collision response calculations are replaced by simpler calculations based on the statistical signature. In addition, based on our statistical simulator, we develop a mixed rigid body simulator that combines an impulse-based with a statistically-based collision response method. This allows us to maintain high accuracy in important parts of the scene while achieving greater efficiency by simplifying less important parts of the simulation. The resulting system gives speedups of more than an order of magnitude on several large rigid body simulations while maintaining high accuracy in key places and capturing overall statistical behavior in other places. Also, we introduce two methods for directing pile behavior to form the desired shapes. To fill up the space inside the desired shapes and maintain the stability of the desired pile shapes, our methods analyze the configurations and status of all objects and properly select some candidates to have their degrees of freedom (DOFs) reduced. Our first method utilizes the idea of angles of repose to perform the analysis. According to the desired angle of repose, we create an additional spatial structure to track the piling status and select suitable objects to reduce their DOFs. In our second method, we adapt equilibrium analysis in a local scheme to find “stable” objects of the stacking structure. Then, we restrict their DOFs by adding constraints on them for stabilizing the structure. Overall, our directing methods generate a wider variety of piled structures than possible with strict physically-based simulation

Algorithms for Geometric Optimization and Enrichment in Industrialized Building Construction

The burgeoning use of industrialized building construction, coupled with advances in digital technologies, is unlocking new opportunities to improve the status quo of construction projects being over-budget, delayed and having undesirable quality. Yet there are still several objective barriers that need to be overcome in order to fully realize the full potential of these innovations. Analysis of literature and examples from industry reveal the following notable barriers: (1) geometric optimization methods need to be developed for the stricter dimensional requirements in industrialized construction, (2) methods are needed to preserve model semantics during the process of generating an updated as-built model, (3) semantic enrichment methods are required for the end-of-life stage of industrialized buildings, and (4) there is a need to develop pragmatic approaches for algorithms to ensure they achieve required computational efficiency. The common thread across these examples is the need for developing algorithms to optimize and enrich geometric models. To date, a comprehensive approach paired with pragmatic solutions remains elusive. This research fills this gap by presenting a new approach for algorithm development along with pragmatic implementations for the industrialized building construction sector. Computational algorithms are effective for driving the design, analysis, and optimization of geometric models. As such, this thesis develops new computational algorithms for design, fabrication and assembly, onsite construction, and end-of-life stages of industrialized buildings. A common theme throughout this work is the development and comparison of varied algorithmic approaches (i.e., exact vs. approximate solutions) to see which is optimal for a given process. This is implemented in the following ways. First, a probabilistic method is used to simulate the accumulation of dimensional tolerances in order to optimize geometric models during design. Second, a series of exact and approximate algorithms are used to optimize the topology of 2D panelized assemblies to minimize material use during fabrication and assembly. Third, a new approach to automatically update geometric models is developed whereby initial model semantics are preserved during the process of generating an as-built model. Finally, a series of algorithms are developed to semantically enrich geometric models to enable industrialized buildings to be disassembled and reused. The developments made in this research form a rational and pragmatic approach to addressing the existing challenges faced in industrialized building construction. Such developments are shown not only to be effective in improving the status quo in the industry (i.e., improving cost, reducing project duration, and improving quality), but also for facilitating continuous innovation in construction. By way of assessing the potential impact of this work, the proposed algorithms can reduce rework risk during fabrication and assembly (65% rework reduction in the case study for the new tolerance simulation algorithm), reduce waste during manufacturing (11% waste reduction in the case study for the new panel unfolding and nesting algorithms), improve accuracy and automation of as-built model generation (model error reduction from 50.4 mm to 5.7 mm in the case study for the new parametric BIM updating algorithms), reduce lifecycle cost for adapting industrialized buildings (15% reduction in capital costs in the computational building configurator) and reducing lifecycle impacts for reusing structural systems from industrialized buildings (between 54% to 95% reduction in average lifecycle impacts for the approach illustrated in Appendix B). From a computational standpoint, the novelty of the algorithms developed in this research can be described as follows. Complex geometric processes can be codified solely on the innate properties of geometry – that is, by parameterizing geometry and using methods such as combinatorial optimization, topology can be optimized and semantics can be automatically enriched for building assemblies. Employing the use of functional discretization (whereby continuous variable domains are converted into discrete variable domains) is shown to be highly effective for complex geometric optimization approaches. Finally, the algorithms encapsulate and balance the benefits posed by both parametric and non-parametric schemas, resulting in the ability to achieve both high representational accuracy and semantically rich information (which has previously not been achieved or demonstrated). In summary, this thesis makes several key improvements to industrialized building construction. One of the key findings is that rather than pre-emptively determining the best suited algorithm for a given process or problem, it is often more pragmatic to derive both an exact and approximate solution and then decide which is optimal to use for a given process. Generally, most tasks related to optimizing or enriching geometric models is best solved using approximate methods. To this end, this research presents a series of key techniques that can be followed to improve the temporal performance of algorithms. The new approach for developing computational algorithms and the pragmatic demonstrations for geometric optimization and enrichment are expected to bring the industry forward and solve many of the current barriers it faces