Procedural function-based modelling of volumetric microstructures

We propose a new approach to modelling heterogeneous objects containing internal volumetric structures with size of details orders of magnitude smaller than the overall size of the object. The proposed function-based procedural representation provides compact, precise, and arbitrarily parameterised models of coherent microstructures, which can undergo blending, deformations, and other geometric operations, and can be directly rendered and fabricated without generating any auxiliary representations (such as polygonal meshes and voxel arrays). In particular, modelling of regular lattices and cellular microstructures as well as irregular porous media is discussed and illustrated. We also present a method to estimate parameters of the given model by fitting it to microstructure data obtained with magnetic resonance imaging and other measurements of natural and artificial objects. Examples of rendering and digital fabrication of microstructure models are presented

Managing Diversity and Many Objectives in Evolutionary Design

This thesis proposes a new approach to evolving a diversity of high-quality solutions for problems having many objectives. Mouret and Clune's MAP-Elites algorithm has been proposed as a way to evolve an assortment of diverse solutions to a problem. We extend MAP-Elites in a number of ways. Firstly, we introduce a many-objective strategy called sum-of-ranks, which enables problems with many objectives (4 and more) to be considered in the MAP. Secondly, we enhance MAP-Elites by extending it with multiple solutions per "grid" cell (the original MAP-Elites saves only a single solution per cell). A few different ways of selecting cell members for reproduction are also considered. We test the new MAP-Elites strategies on the evolutionary art application of image generation. Using procedural textures, genetic programming is used with upwards of 15 lightweight image features to guide fitness. The goal is to evolve images that share image features with a given target image. Our experiments show that the new MAP-Elites algorithms produce a large number of diverse solutions of varying quality. The extended MAP-Elites algorithm is also statistically competitive compared to vanilla GP in this application domain

Non-parametric synthesis of laminar volumetric texture

International audienceThe goal of this paper is to evaluate several extensions of Wei and Levoy's algorithm for the synthesis of laminar volumetric textures constrained only by a single 2D sample. Hence, we shall also review in a unified form the improved algorithm proposed by Kopf et al. and the particular histogram matching approach of Chen and Wang. Developing a genuine quantitative study we are able to compare the performances of these algorithms that we have applied to the synthesis of volumetric structures of dense carbons. The 2D samples are lattice fringe images obtained by high resolution transmission electronic microscopy (HRTEM)

Smart Cities: Inverse Design of 3D Urban Procedural Models with Traffic and Weather Simulation

Urbanization, the demographic transition from rural to urban, has changed how we envision and share the world. From just one-fourth of the population living in cities one hundred years ago, now more than half of the population does, and this ratio is expected to grow in the near future. Creating more sustainable, accessible, safe, and enjoyable cities has become an imperative

Distributed MAP-Elites and its Application in Evolutionary Design

Quality-Diversity search is the process of finding diverse solutions within the search space which do not sacrifice performance. MAP-Elites is a quality-diversity algorithm which measures n phenotypes/behaviours of a solution and places it into an $n$-dimensional hypercube based off its phenotype values. This thesis proposes an approach to addressing MAP-Elites' problem of exponential growth of hypercubes. The exponential growth of evaluation and computational time as the phenotypes/behaviours grow is potentially worse for optimization performance. The exponential growth in individuals results in the user being given too many candidate solutions at the end of processing. Therefore, MAP-Elites highlights diversity, but with the exponential growth, the said diversity is arguably impractical. This research proposes an enhancement to MAP-Elites with Distributed island-model evolution. This will introduce a linear growth in population as well as a reasonable number of candidate solutions to consider. Each island consists of a two dimensional MAP which allows for a realistic analysis and visualization of these individuals. Since the system increases on a linear scale, and MAP-Elites on an exponential scale, high-dimensional problems will show an even greater decrease in total candidate solution counts, which aids in the realistic analysis of a run. This system will then be tested on procedural texture generation with multiple computer vision fitness functions. This Distributed MAP-Elites algorithm was tested against vanilla GP, island-model evolution, and traditional MAP-Elites on multiple fitness functions and target images. The proposed algorithm was found, at the very minimum, to be competitive in fitness to the other algorithms and in some cases outperformed them. On top of this performance, when visually observing the best solutions, the algorithm was found to have been able to produce visually interesting textures

Customizing Experiences for Mobile Virtual Reality

A criação manual de conteúdo para um jogo é um processo demorado e trabalhoso que requer um conjunto de habilidades diversi cado (normalmente designers, artistas e programadores) e a gestão de diferentes recursos (hardware e software especializados). Dado que o orçamento, tempo e recursos são frequentemente muito limitados, os projetos poderiam bene ciar de uma solução que permitisse poupar e investir noutros aspectos do desenvolvimento. No contexto desta tese, abordamos este desa o sugerindo a criação de pacotes especí cos para a geração de conteúdo per sonalizável, focados em aplicações de Realidade Virtual (RV) móveis. Esta abordagem divide o problema numa solução com duas facetas: em primeiro lugar, a Geração Procedural de Conteúdo, alcançada através de métodos convencionais e pela utilização inovadora de Grandes Modelos de Lin guagem (normalmente conhecidos por Large Language Models). Em segundo lugar, a Co-Criação de Conteúdo, que enfatiza o desenvolvimento colaborativo de conteúdo. Adicionalmente, dado que este trabalho se foca na compatibilidade com RV móvel, as limitações de hardware associadas a capacetes de RV autónomos (standalone VR Headsets) e formas de as ultrapassar são também abordadas. O conteúdo será gerado utilizando métodos actuais em geração procedural e facilitando a co-criação de conteúdo pelo utilizador. A utilização de ambas estas abordagens resulta em ambi entes, objectivos e conteúdo geral mais re-jogáveis com muito menos desenho. Esta abordagem está actualmente a ser aplicada no desenvolvimento de duas aplicações de RV distintas. A primeira, AViR, destina-se a oferecer apoio psicológico a indivíduos após a perda de uma gravidez. A se gunda, EmotionalVRSystem, visa medir as variações nas respostas emocionais dos participantes induzidas por alterações no ambiente, utilizando tecnologia EEG para leituras precisas

From 3D Models to 3D Prints: an Overview of the Processing Pipeline

Due to the wide diffusion of 3D printing technologies, geometric algorithms for Additive Manufacturing are being invented at an impressive speed. Each single step, in particular along the Process Planning pipeline, can now count on dozens of methods that prepare the 3D model for fabrication, while analysing and optimizing geometry and machine instructions for various objectives. This report provides a classification of this huge state of the art, and elicits the relation between each single algorithm and a list of desirable objectives during Process Planning. The objectives themselves are listed and discussed, along with possible needs for tradeoffs. Additive Manufacturing technologies are broadly categorized to explicitly relate classes of devices and supported features. Finally, this report offers an analysis of the state of the art while discussing open and challenging problems from both an academic and an industrial perspective.Comment: European Union (EU); Horizon 2020; H2020-FoF-2015; RIA - Research and Innovation action; Grant agreement N. 68044