Abstract We present a physically‐informed segmentation pipeline for producing fabric formwork for the casting and molding of arbitrary 3D objects. Fabric formworks are molds made by stitching together patches of textile fabric. The mechanical flexibility offered by these molds aids the fabrication of unconventional and complex geometries and allows for greater transportation ease for on‐site fabrication tasks. We employ an isotropic material model to estimate maximal strain directions that result when casting fluid is poured into the formwork. Our physically driven segmentation approach ensures seams and fiber directions align with these maximal strains. Experimental observations indicate that this alignment strategy significantly reduces twisting and shearing artifacts associated with the orthotropic deformation of woven fabrics. Aligning seams with strain directions further limits deformation of the formwork, improving fidelity to the input model. Moreover, our segmentation improves upon that of [ZFS*19] by promoting smoother seams and quad‐like patches, reducing the time and expertise needed to construct the formwork. We validate the efficacy of our pipeline by fabricating and simulating shapes of varying complexity, showing superior geometric reconstruction and fabrication ease.

Slipped and tucked stitches introduce small areas of deformation that compound and result in emergent textures on knitted fabrics. When used together with color changes and ladders, these can also produce dramatic colorwork and openwork effects. However, designing slip and tuck colorwork patterns is challenging due to the complex interactions between operations, yarns, and deformations. We present KnitScape, a browser-based tool for design and simulation of stitch patterns for knitting. KnitScape provides a design interface to specify 1) operation repeats, 2) color changes, and 3) needle positions. These inputs are used to build a graph of yarn topology and run a yarn-level spring simulation. This enables visualization of the deformation that arises from slip and tuck operations. Through its design tool and simulation, KnitScape enables rapid exploration of a complex colorwork design space. We demonstrate KnitScape with a series of example swatches.

Joint injuries, and their long-term consequences, present a substantial global health burden. Wearable prophylactic braces are an attractive potential solution to reduce the incidence of joint injuries by limiting joint movements that are related to injury risk. Given human motion and ground reaction forces, we present a computational framework that enables the design of personalized braces by optimizing the distribution of microstructures and elasticity. As varied brace designs yield different reaction forces that influence kinematics and kinetics analysis outcomes, the optimization process is formulated as a differentiable end-to-end pipeline in which the design domain of microstructure distribution is parameterized onto a neural network. The optimized distribution of microstructures is obtained via a self-learning process to determine the network coefficients according to a carefully designed set of losses and the integrated biomechanical and physical analyses. Since knees and ankles are the most commonly injured joints, we demonstrate the effectiveness of our pipeline by designing, fabricating, and testing prophylactic braces for the knee and ankle to prevent potentially harmful joint movements.

We present a new class of curved block-based line structures whose component chains are flexible when separated, and provably rigid when assembled together into an interlocking double chain. The joints are inspired by traditional zippers, where a binding fabric or mesh connects individual teeth. Unlike traditional zippers, the joint design produces a rigid interlock with programmable curvature. This allows fairly strong curved structures to be built out of easily stored flexible chains. In this paper, we introduce a pipeline for generating these curved structures using a novel block design template based on revolute joints. Mesh embedded in these structures maintains block spacing and assembly order. We evaluate the rigidity of the curved structures through mechanical performance testing and demonstrate several applications.

In chart-based programming environments for machine knitting, patterns are specified at a low level by placing operations on a grid. This highly manual workflow makes it challenging to iterate on design elements such as cables, colorwork, and texture. While vector-based abstractions for knitting design elements may facilitate higher-level manipulation, they often include interdependencies which require stitch-level reconciliation. To address this, we contribute a new way of specifying knits with blended vector and raster primitives. Our abstraction supports the design of interdependent elements like colorwork and texture. We have implemented our blended raster/vector specification in a direct manipulation design tool where primitives are layered and rasterized, allowing for simulation of the resulting knit structure and generation of machine instructions. Through examples, we show how our approach enables higher-level manipulation of various knitting techniques, including intarsia colorwork, short rows, and cables. Specifically, we show how our tool supports the design of complex patterns including origami pleat patterns and capacitive sensor patches.

This paper presents a learning based planner for computing optimized 3D printing toolpaths on prescribed graphs, the challenges of which include the varying graph structures on different models and the large scale of nodes & edges on a graph. We adopt an on-the-fly strategy to tackle these challenges, formulating the planner as a Deep Q-Network (DQN) based optimizer to decide the next 'best' node to visit. We construct the state spaces by the Local Search Graph (LSG) centered at different nodes on a graph, which is encoded by a carefully designed algorithm so that LSGs in similar configurations can be identified to re-use the earlier learned DQN priors for accelerating the computation of toolpath planning. Our method can cover different 3D printing applications by defining their corresponding reward functions. Toolpath planning problems in wire-frame printing, continuous fiber printing, and metallic printing are selected to demonstrate its generality. The performance of our planner has been verified by testing the resultant toolpaths in physical experiments. By using our planner, wire-frame models with up to 4.2k struts can be successfully printed, up to 93.3% of sharp turns on continuous fiber toolpaths can be avoided, and the thermal distortion in metallic printing can be reduced by 24.9%.

The physical plausibility of human motions is vital to various applications in fields including but not limited to graphics, animation, robotics, vision, biomechanics, and sports science. While fully simulating human motions with physics is an extreme challenge, we hypothesize that we can treat this complexity as a black box in a data-driven manner if we focus on the ground contact, and have sufficient observations of physics and human activities in the real world. To prove our hypothesis, we present GroundLink, a unified dataset comprised of captured ground reaction force (GRF) and center of pressure (CoP) synchronized to standard kinematic motion captures. GRF and CoP of GroundLink are not simulated but captured at high temporal resolution using force platforms embedded in the ground for uncompromising measurement accuracy. This dataset contains 368 processed motion trials (∼ 1.59M recorded frames) with 19 different movements including locomotion and weight-shifting actions such as tennis swings to signify the importance of capturing physics paired with kinematics. GroundLinkNet, our benchmark neural network model trained with GroundLink, supports our hypothesis by predicting GRFs and CoPs accurately and plausibly on unseen motions from various sources. The dataset, code, and benchmark models are made public for further research on various downstream tasks leveraging the rich physics information at https://csr.bu.edu/groundlink/.

In this paper, we present a new computational pipeline for designing and fabricating 4D garments as knitwear that considers comfort during body movement. This is achieved by careful control of elasticity distribution to reduce uncomfortable pressure and unwanted sliding caused by body motion. We exploit the ability to knit patterns in different elastic levels by single-jersey jacquard (SJJ) with two yarns. We design the distribution of elasticity for a garment by physics-based computation, the optimized elasticity on the garment is then converted into instructions for a digital knitting machine by two algorithms proposed in this paper. Specifically, a graph-based algorithm is proposed to generate knittable stitch meshes that can accurately capture the 3D shape of a garment, and a tiling algorithm is employed to assign SJJ patterns on the stitch mesh to realize the designed distribution of elasticity. The effectiveness of our approach is verified on simulation results and on specimens physically fabricated by knitting machines.

We present a novel haptic and audio feedback device that allows blind and visually impaired (BVI) users to understand circuit diagrams. TangibleCircuits allows users to interact with a 3D printed tangible model of a circuit which provides audio tutorial directions while being touched. Our system comprises an automated parsing algorithm which extracts 3D printable models as well as an audio interfaces from a Fritzing diagram. To better understand the requirements of designing technology to assist BVI users in learning hardware computing, we conducted a series of formative inquiries into the accessibility limitations of current circuit tutorial technologies. In addition, we derived insights and design considerations gleaned from conducting a formal comparative user study to understand the effectiveness of TangibleCircuits as a tutorial system. We found that BVI users were better able to understand the geometric, spatial and structural circuit information using TangibleCircuits, as well as enjoyed learning with our tool.

This paper presents a method of computing free motions of a planar assembly of rigid bodies connected by loose joints. Joints are modeled using local distance constraints, which are then linearized with respect to configuration space velocities, yielding a linear programming formulation that allows analysis of systems with thousands of rigid bodies. Potential applications include analysis of collections of modular robots, structural stability perturbation analysis, tolerance analysis for mechanical systems, and formation control of mobile robots.

Members of the blind and visually impaired community rely heavily on tactile illustrations - raised line graphics on paper that are felt by hand - to understand geometric ideas in school textbooks, depict a story in children's books, or conceptualize exhibits in museums. However, these illustrations often fail to achieve their goals, in large part due to the lack of understanding in how 3D shapes can be represented in 2D projections. This paper describes a new technique to design tactile illustrations considering the needs of blind individuals. Successful illustration design of 3D objects presupposes identification and combination of important information in topology and geometry. We propose a twofold approach to improve shape understanding. First, we introduce a part-based multi-projection rendering strategy to display geometric information of 3D shapes, making use of canonical viewpoints and removing reliance on traditional perspective projections. Second, curvature information is extracted from cross sections and embedded as textures in our illustrations.

We present an inverse design tool for fabric formwork - a process where flat panels are sewn together to form a fabric container for casting a plaster sculpture. Compared to 3D printing techniques, the benefit of fabric formwork is its properties of low-cost and easy transport. The process of fabric formwork is akin to molding and casting but having a soft boundary. Deformation of the fabric container is governed by force equilibrium between the pressure forces from liquid fill and tension in the stretched fabric. The final result of fabrication depends on the shapes of the flat panels, the fabrication orientation and the placement of external supports. Our computational framework generates optimized flat panels and fabrication orientation with reference to a target shape, and determines effective locations for external supports. We demonstrate the function of this design tool on a variety of models with different shapes and topology. Physical fabrication is also demonstrated to validate our approach.

Abstract Watercolor paintings have a unique look that mixes subtle color gradients and sophisticated diffusion patterns. This makes them immediately recognizable and gives them a unique appeal. Creating such paintings requires advanced skills that are beyond the reach of most people. Even for trained artists, producing several copies of a painting is a tedious task. One can resort to scanning an existing painting and printing replicas, but these are all identical and have lost an essential characteristic of a painting, its uniqueness. We address these two issues with a technique to fabricate woodblocks that we later use to create watercolor prints. The woodblocks can be reused to produce multiple copies but each print is unique due to the physical process that we introduce. We also design an image processing pipeline that helps users to create the woodblocks and describe a protocol that produces prints by carefully controlling the interplay between the paper, ink pigments, and water so that the final piece depicts the desired scene while exhibiting the distinctive features of watercolor. Our technique enables anyone with the resources to produce watercolor prints.

This paper considers an assembly problem. Let there be two interlocking parts, only one of which may be cut into pieces. How many pieces should we cut the divisible part into to separate the parts using a sequence of rigid-body motions? In this initial exploration, we primarily consider 2-D polygonal parts. This paper presents an algorithm that computes a lower bound on the number of pieces that the divisible part must be cut into. This paper also presents a complete algorithm that constructs a set of cuts and a motion plan for disassembly, yielding an upper bound on the required number of pieces. Applications of the future extension of this paper to 3-D may include robot self-assembly, interlocking 3-D model design, search-and-rescue, packaging, and robotic surgery.

Despite rapid advances in 3D printing, fabricating large, durable and robust artifacts is impractical with current technology. We focus on a particularly challenging environment-scale artifact: rock climbing routes. We propose a prototype fabrication method to replicate part of an outdoor climbing route and enable the same sensorimotor experience in an indoor gym. We start with 3D reconstruction of the rock wall using multi-view stereo and use reference videos of a climber in action to identify localized rock features that are necessary for ascent. We create 3D models akin to traditional indoor climbing holds, fabricated using rapid prototyping, molding and casting techniques. This results in robust holds accurately replicating the features and configuration of the original rock route. Validation was performed on two rock climbing sites in New Hampshire and Utah. We verified our results by comparing climbers' moves on the indoor replicas and original outdoor routes.

This paper introduces a novel method for designing personalized orthopedic casts which are aware of thermal-comfort while satisfying mechanical requirements. Our pipeline starts from thermal images taken by an infrared camera, by which the distribution of thermal-comfort sensitivity is generated on the surface of a 3D scanned model. We formulate a hollowed Voronoi tessellation pattern to represent the covered region for a web-like cast design. The pattern is further optimized according to the thermal-comfort sensitivity calculated from thermal images. Working together with a thickness variation method, we generate a solid model for a personalized cast maximizing both thermal comfort and mechanical stiffness. To demonstrate the effectiveness of our approach, 3D printed models of personalized casts are tested on body parts of different individuals.

Abstract This paper introduces a design and fabrication pipeline for creating floating forms. Our method optimizes for buoyant equilibrium and stability of complex 3D shapes, applying a voxel‐carving technique to control the mass distribution. The resulting objects achieve a desired floating pose defined by a user‐specified waterline height and orientation. In order to enlarge the feasible design space, we explore novel ways to load the interior of a design using prefabricated components and casting techniques. 3D printing is employed for high‐precision fabrication. For larger scale designs we introduce a method for stacking lasercut planar pieces to create 3D objects in a quick and economic manner. We demonstrate fabricated designs of complex shape in a variety of floating poses.

Abstract We present a method to design the deformation behavior of 3D printed models by an interactive tool, where the variation of bending elasticity at different regions of a model is realized by a change in shell thickness. Given a soft material to be used in 3D printing, we propose an experimental setup to acquire the bending behavior of this material on tubes with different diameters and thicknesses. The relationship between shell thickness and bending elasticity is stored in an echo state network using the acquired dataset. With the help of the network, an interactive design tool is developed to generate non‐uniformly hollowed models to achieve desired bending behaviors. The effectiveness of this method is verified on models fabricated by different 3D printers by studying whether their physical deformation can match the designed target shape.

This paper presents an interactive design interface for three-dimensional free-form musical wind instruments. The sound of a wind instrument is governed by the acoustic resonance as a result of complicated interactions of sound waves and internal geometries of the instrument. Thus, creating an original free-form wind instrument by manual methods is a challenging problem. Our interface provides interactive sound simulation feedback as the user edits, allowing exploration of original wind instrument designs. Sound simulation of a 3D wind musical instrument is known to be computationally expensive. To overcome this problem, we first model the wind instruments as a passive resonator, where we ignore coupled oscillation excitation from the mouthpiece. Then we present a novel efficient method to estimate the resonance frequency based on the boundary element method by formulating the resonance problem as a minimum eigenvalue problem. Furthermore, we can efficiently compute an approximate resonance frequency using a new technique based on a generalized eigenvalue problem. The designs can be fabricated using a 3D printer, thus we call the results "print-wind instruments" in association with woodwind instruments. We demonstrate our approach with examples of unconventional shapes performing familiar songs.

This paper introduces a perceptual model for determining 3D printing orientations. Additive manufacturing methods involving low-cost 3D printers often require robust branching support structures to prevent material collapse at overhangs. Although the designed shape can successfully be made by adding supports, residual material remains at the contact points after the supports have been removed, resulting in unsightly surface artifacts. Moreover, fine surface details on the fabricated model can easily be damaged while removing supports. To prevent the visual impact of these artifacts, we present a method to find printing directions that avoid placing supports in perceptually significant regions. Our model for preference in 3D printing direction is formulated as a combination of metrics including area of support, visual saliency, preferred viewpoint and smoothness preservation. We develop a training-and-learning methodology to obtain a closed-form solution for our perceptual model and perform a large-scale study. We demonstrate the performance of this perceptual model on both natural and man-made objects.

Self-supporting structures are prominent in historical and contemporary architecture due to advantageous structural properties and efficient use of material. Computer graphics research has recently contributed new design tools that allow creating and interactively exploring self-supporting freeform designs. However, the physical construction of such freeform structures remains challenging, even on small scales. Current construction processes require extensive formwork during assembly, which quickly leads to prohibitively high construction costs for realizations on a building scale. This greatly limits the practical impact of the existing freeform design tools. We propose to replace the commonly used dense formwork with a sparse set of temporary chains. Our method enables gradual construction of the masonry model in stable sections and drastically reduces the material requirements and construction costs. We analyze the input using a variational method to find stable sections, and devise a computationally tractable divide-and-conquer strategy for the combinatorial problem of finding an optimal construction sequence. We validate our method on 3D printed models, demonstrate an application to the restoration of historical models, and create designs of recreational, collaborative self-supporting puzzles.

Spinning tops and yo-yos have long fascinated cultures around the world with their unexpected, graceful motions that seemingly elude gravity. We present an algorithm to generate designs for spinning objects by optimizing rotational dynamics properties. As input, the user provides a solid 3D model and a desired axis of rotation. Our approach then modifies the mass distribution such that the principal directions of the moment of inertia align with the target rotation frame. We augment the model by creating voids inside its volume, with interior fill represented by an adaptive multi-resolution voxelization. The discrete voxel fill values are optimized using a continuous, nonlinear formulation. Further, we optimize for rotational stability by maximizing the dominant principal moment. We extend our technique to incorporate deformation and multiple materials for cases where internal voids alone are insufficient. Our method is well-suited for a variety of 3D printed models, ranging from characters to abstract shapes. We demonstrate tops and yo-yos that spin surprisingly stably despite their asymmetric appearance.

Imbalance suggests a feeling of dynamism and movement in static objects. It is therefore not surprising that many 3D models stand in impossibly balanced configurations. As long as the models remain in a computer this is of no consequence: the laws of physics do not apply. However, fabrication through 3D printing breaks the illusion: printed models topple instead of standing as initially intended. We propose to assist users in producing novel, properly balanced designs by interactively deforming an existing model. We formulate balance optimization as an energy minimization, improving stability by modifying the volume of the object, while preserving its surface details. This takes place during interactive editing: the user cooperates with our optimizer towards the end result. We demonstrate our method on a variety of models. With our technique, users can produce fabricated objects that stand in one or more surprising poses without requiring glue or heavy pedestals.

In the design of buildings, structural analysis is traditionally performed after the aesthetic design has been determined and has little influence on the overall form. In contrast, this paper presents an approach to guide the form towards a shape that is more structurally sound. Our work is centered on the study of how variations of the geometry might improve structural stability. We define a new measure of structural soundness for masonry buildings as well as cables, and derive its closed-form derivative with respect to the displacement of all the vertices describing the geometry. We start with a gradient descent tool which displaces each vertex along the gradient. We then introduce displacement operators, imposing constraints such as the preservation of orientation or thickness; or setting additional objectives such as volume minimization.

We introduce structural feasibility into procedural modeling of buildings. This allows for more realistic structural models that can be interacted with in physical simulations. While existing structural analysis tools focus heavily on providing an analysis of the stress state, our proposed method automatically tunes a set of designated free parameters to obtain forms that are structurally sound.

Material limitations and fabrication costs generally run at odds with the creativity of architectural design, producing a wealth of challenging computational geometry problems. We have developed an algorithm for solving an important class of fabrication constraints: those associated with planar construction materials such as glass or plywood.Starting with a complex curved input shape, defined as a NURBS or subdivision surface, we use an iterative clustering method to remesh the surface into planar panels following a cost function that is adjusted by the designer. We solved several challenging connectivity issues to ensure that the topology of the resulting mesh matches that of the input surface.The algorithm described in this paper has been implemented and developed in conjunction with an architectural design seminar. How the participants incorporated this tool into their design process was considered. Their important feedback led to key algorithmic and implementation insights as well as many exciting ideas for future exploration. This prototype tool has potential to impact not only architectural design, but also the engineering for general fabrication problems.