Figure 1: We present a method to convert animated digital characters into physically fabricated prototypes. Our physical characters can be actuated using pins, strings, or posed by hand. AbstractWe present a method for fabrication-oriented design of actuated deformable characters that allows a user to automatically create physical replicas of digitally designed characters using rapid manufacturing technologies. Given a deformable character and a set of target poses as input, our method computes a small set of actuators along with their locations on the surface and optimizes the internal material distribution such that the resulting character exhibits the desired deformation behavior. We approach this problem with a dedicated algorithm that combines finite-element analysis, sparse regularization, and constrained optimization. We validate our pipeline on a set of two-and three-dimensional example characters and present results in simulation and physically-fabricated prototypes.
Figure 1: An overview of our design system: the user provides a target shape (left) and sketches seams to indicate desired segment boundaries (2 nd from left). Our system automatically computes flat panels such that the inflated structure (middle) is as close as possible to the target. The generated panels (2 nd from right) can be used to fabricate a physical prototype (right). AbstractWe propose an interactive, optimization-in-the-loop tool for designing inflatable structures. Given a target shape, the user draws a network of seams defining desired segment boundaries in 3D. Our method computes optimally-shaped flat panels for the segments, such that the inflated structure is as close as possible to the target while satisfying the desired seam positions. Our approach is underpinned by physics-based pattern optimization, accurate coarse-scale simulation using tension field theory, and a specialized constraint-optimization method. Our system is fast enough to warrant interactive exploration of different seam layouts, including internal connections, and their effects on the inflated shape. We demonstrate the resulting design process on a varied set of simulation examples, some of which we have fabricated, demonstrating excellent agreement with the design intent. CR Categories: I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling-Physically based modeling
We report the first fully automatic method for discovering microstructure families with extremal physical properties.
Figure 1: Given a target shape (a), we use experimentally-acquired material properties (b) to compute and fabricate an optimal balloon shape (c). Upon inflation, the optimized balloon closely approximates the target (d), whereas inflating a small version of the target (e) results in poor approximation. AbstractThis paper presents an automatic process for fabrication-oriented design of custom-shaped rubber balloons. We cast computational balloon design as an inverse problem: given a target shape, we compute an optimal balloon that, when inflated, approximates the target as closely as possible. To solve this problem numerically, we propose a novel physics-driven shape optimization method, which combines physical simulation of inflatable elastic membranes with a dedicated constrained optimization algorithm. We validate our approach by fabricating balloons designed with our method and comparing their inflated shapes to the results predicted by simulation. An extensive set of manufactured sample balloons demonstrates the shape diversity that can be achieved by our method.
Fig. 1. Our two-scale topology optimization framework allows to optimize continuous material properties mapping to printable microstructures (le ) to fabricate high-resolution functional objects (middle) and minimum compliant structures (right).In this paper we present a novel two-scale framework to optimize the structure and the material distribution of an object given its functional specications. Our approach utilizes multi-material microstructures as low-level building blocks of the object. We start by precomputing the material property gamut -the set of bulk material properties that can be achieved with all material microstructures of a given size. We represent the boundary of this material property gamut using a level set eld. Next, we propose an e cient and general topology optimization algorithm that simultaneously computes an optimal object topology and spatially-varying material properties constrained by the precomputed gamut. Finally, we map the optimal spatially-varying material properties onto the microstructures with the corresponding properties in order to generate a high-resolution printable structure. We demonstrate the e cacy of our framework by designing, optimizing, and fabricating objects in di erent material property spaces on the level of a trillion voxels, i.e several orders of magnitude higher than what can be achieved with current systems.
Fig. 1. Our two-scale topology optimization framework allows to optimize continuous material properties mapping to printable microstructures (le ) to fabricate high-resolution functional objects (middle) and minimum compliant structures (right).In this paper we present a novel two-scale framework to optimize the structure and the material distribution of an object given its functional specications. Our approach utilizes multi-material microstructures as low-level building blocks of the object. We start by precomputing the material property gamut -the set of bulk material properties that can be achieved with all material microstructures of a given size. We represent the boundary of this material property gamut using a level set eld. Next, we propose an e cient and general topology optimization algorithm that simultaneously computes an optimal object topology and spatially-varying material properties constrained by the precomputed gamut. Finally, we map the optimal spatially-varying material properties onto the microstructures with the corresponding properties in order to generate a high-resolution printable structure. We demonstrate the e cacy of our framework by designing, optimizing, and fabricating objects in di erent material property spaces on the level of a trillion voxels, i.e several orders of magnitude higher than what can be achieved with current systems.
Upcoming actuation systems will be required to perform multiple tightly coupled functions analogous to their natural counterparts; e.g., the ability to control displacements and high-resolution appearance simultaneously is necessary for mimicking the camouflage seen in cuttlefish. Creating integrated actuation systems is challenging owing to the combined complexity of generating high-dimensional designs and developing multifunctional materials and their associated fabrication processes. Here, we present a complete toolkit consisting of multiobjective topology optimization (for design synthesis) and multimaterial drop-on-demand three-dimensional printing for fabricating complex actuators (>106 design dimensions). The actuators consist of soft and rigid polymers and a magnetic nanoparticle/polymer composite that responds to a magnetic field. The topology optimizer assigns materials for individual voxels (volume elements) while simultaneously optimizing for physical deflection and high-resolution appearance. Unifying a topology optimization-based design strategy with a multimaterial fabrication process enables the creation of complex actuators and provides a promising route toward automated, goal-driven fabrication.
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