31 research outputs found
HexBox: Interactive Box Modeling of Hexahedral Meshes
We introduce HexBox, an intuitive modeling method and interactive tool for creating and editing hexahedral meshes. Hexbox brings the major and widely validated surface modeling paradigm of surface box modeling into the world of hex meshing. The main idea is to allow the user to box-model a volumetric mesh by primarily modifying its surface through a set of topological and geometric operations. We support, in particular, local and global subdivision, various instantiations of extrusion, removal, and cloning of elements, the creation of non-conformal or conformal grids, as well as shape modifications through vertex positioning, including manual editing, automatic smoothing, or, eventually, projection on an externally-provided target surface. At the core of the efficient implementation of the method is the coherent maintenance, at all steps, of two parallel data structures: a hexahedral mesh representing the topology and geometry of the currently modeled shape, and a directed acyclic graph that connects operation nodes to the affected mesh hexahedra. Operations are realized by exploiting recent advancements in grid- based meshing, such as mixing of 3-refinement, 2-refinement, and face-refinement, and using templated topological bridges to enforce on-the-fly mesh conformity across pairs of adjacent elements. A direct manipulation user interface lets users control all operations. The effectiveness of our tool, released as open source to the community, is demonstrated by modeling several complex shapes hard to realize with competing tools and techniques
LIPIcs, Volume 258, SoCG 2023, Complete Volume
LIPIcs, Volume 258, SoCG 2023, Complete Volum
Design for an Increasingly Protean Machine
Data-driven, rather than hypothesis-driven, approaches to robot design are becoming increasingly widespread, but they remain narrowly focused on tuning the parameters of control software (neural network synaptic weights) inside an overwhelmingly static and presupposed body. Meanwhile, an efflorescence of new actuators and metamaterials continue to broaden the ways in which machines are free to move and morph, but they have yet to be adopted by useful robots because the design and control of metamorphosing body plans is extremely non-intuitive. This thesis unites these converging yet previously segregated technologies by automating the design of robots with physically malleable hardware, which we will refer to as protean machines, named after Proteus of Greek mythology.
This thesis begins by proposing an ontology of embodied agents, their physical features, and their potential ability to purposefully change each one in space and time. A series of experiments are then documented in which increasingly more of these features (structure, shape, and material properties) were allowed to vary across increasingly more timescales (evolution, development, and physiology), and collectively optimized to facilitate adaptive behavior in a simulated physical environment. The utility of increasingly protean machines is demonstrated by a concomitant increase in both the performance and robustness of the final, optimized system. This holds true even if its ability to change is temporarily removed by fabricating the system in reality, or by “canalization”: the tendency for plasticity to be supplanted by good static traits (an inductive bias) for the current environment. Further, if physical flexibility is retained rather than canalized, it is shown how protean machines can, under certain conditions, achieve a form of hyper-robustness: the ability to self-edit their own anatomy to “undo” large deviations from the environments in which their control policy was originally optimized.
Some of the designs that evolved in simulation were manufactured in reality using hundreds of highly deformable silicone building blocks, yielding shapeshifting robots. Others were built entirely out of biological tissues, derived from pluripotent Xenopus laevis stem cells, yielding computer-designed organisms (dubbed “xenobots”). Overall, the results shed unique light on questions about the evolution of development, simulation-to-reality transfer of physical artifacts, and the capacity for bioengineering new organisms with useful functions
Crafting chaos: computational design of contraptions with complex behaviour
The 2010s saw the democratisation of digital fabrication technologies. Although this phenomenon made fabrication more accessible, physical assemblies displaying a complex behaviour are still difficult to design. While many methods support the creation of complex shapes and assemblies, managing a complex behaviour is often assumed to be a tedious aspect of the design process. As a result, the complex parts of the behaviour are either deemed negligible (when possible) or managed directly by the software, without offering much fine-grained user control. This thesis argues that efficient methods can support designers seeking complex behaviours by increasing their level of control over these behaviours. To demonstrate this, I study two types of artistic devices that are particularly challenging to design: drawing machines, and chain reaction contraptions. These artefacts’ complex behaviour can change dramatically even as their components are moved by a small amount. The first case study aims to facilitate the exploration and progressive refinement of complex patterns generated by drawing machines under drawing-level user-defined constraints. The approach was evaluated with a user study, and several machines drawing the expected pattern were fabricated. In the second case study, I propose an algorithm to optimise the layout of complex chain reaction contraptions described by a causal graph of events in order to make them robust to uncertainty. Several machines optimised with this method were successfully assembled and run. This thesis makes the following contributions: (1) support complex behaviour specifications; (2) enable users to easily explore design variations that respect these specifications; and (3) optimise the layout of a physical assembly to maximise the probability of real-life success
Loopy Cuts: Surface-Field Aware Block Decomposition for Hex-Meshing.
We present a new fully automatic block-decomposition hexahedral meshing
algorithm capable of producing high quality meshes that strictly preserve
feature curve networks on the input surface and align with an input surface
cross-field. We produce all-hex meshes on the vast majority of inputs, and
introduce localized non-hex elements only when the surface feature network
necessitates those. The input to our framework is a closed surface with a
collection of geometric or user-demarcated feature curves and a feature-aligned
surface cross-field. Its output is a compact set of blocks whose edges
interpolate these features and are loosely aligned with this cross-field. We
obtain this block decomposition by cutting the input model using a collection
of simple cutting surfaces bounded by closed surface loops. The set of cutting
loops spans the input feature curves, ensuring feature preservation, and is
obtained using a field-space sampling process. The computed loops are uniformly
distributed across the surface, cross orthogonally, and are loosely aligned
with the cross-field directions, inducing the desired block decomposition. We
validate our method by applying it to a large range of complex inputs and
comparing our results to those produced by state-of-the-art alternatives.
Contrary to prior approaches, our framework consistently produces high-quality
field aligned meshes while strictly preserving geometric or user-specified
surface features
Recommended from our members
Geometrically Exact and Analysis Suitable Mesh Generation Using Rational Bernstein–Bezier Elements
This dissertation presents two novel contributions to the fields of isogeometric analysis and p-version finite elements. First, we present a framework for geometrically exact volumetric mesh generation. By leveraging ideas from both traditional mesh generation as well as isogeometric analysis, we develop a framework for volumetric mesh generation using rational Bernstein--BĂ©zier discretizations. Within this framework, we provide a set of easily verifiable sufficient conditions for guaranteeing that a mesh will be geometrically exact. Second, we develop a complete theory of mesh quality for these rational Bernstein--BĂ©zier elements. From this, we derive a set of easily computable mesh quality metrics for verifying that a rational Bernstein--BĂ©zier discretization will be analysis suitable