ACM Transactions on Graphics

We present an interactive design system to create functional mechanical objects. Our computational approach allows novice users to retarget an existing mechanical template to a user-specified input shape. Our proposed representation for a mechanical template encodes a parameterized mechanism, mechanical constraints that ensure a physically valid configuration, spatial relationships of mechanical parts to the user-provided shape, and functional constraints that specify an intended functionality. We provide an intuitive interface and optimization-in-the-loop approach for finding a valid configuration of the mechanism and the shape to ensure that higher-level functional goals are met. Our algorithm interactively optimizes the mechanism while the user manipulates the placement of mechanical components and the shape. Our system allows users to efficiently explore various design choices and to synthesize customized mechanical objects that can be fabricated with rapid prototyping technologies. We demonstrate the efficacy of our approach by retargeting various mechanical templates to different shapes and fabricating the resulting functional mechanical objects

Computational Design and Optimization of Non-Circular Gears

We study a general form of gears known as non‐circular gears that can transfer periodic motion with variable speed through their irregular shapes and eccentric rotation centers. To design functional non‐circular gears is nontrivial, since the gear pair must have compatible shape to keep in contact during motion, so the driver gear can push the follower to rotate via a bounded torque that the motor can exert. To address the challenge, we model the geometry, kinematics, and dynamics of non‐circular gears, formulate the design problem as a shape optimization, and identify necessary independent variables in the optimization search. Taking a pair of 2D shapes as inputs, our method optimizes them into gears by locating the rotation center on each shape, minimally modifying each shape to form the gear's boundary, and constructing appropriate teeth for gear meshing. Our optimized gears not only resemble the inputs but can also drive the motion with relatively small torque. We demonstrate our method's usability by generating a rich variety of non‐circular gears from various inputs and 3D printing several of the

Computational design of skinned Quad-Robots

We present a computational design system that assists users to model, optimize, and fabricate quad-robots with soft skins. Our system addresses the challenging task of predicting their physical behavior by fully integrating the multibody dynamics of the mechanical skeleton and the elastic behavior of the soft skin. The developed motion control strategy uses an alternating optimization scheme to avoid expensive full space time-optimization, interleaving space-time optimization for the skeleton, and frame-by-frame optimization for the full dynamics. The output are motor torques to drive the robot to achieve a user prescribed motion trajectory. We also provide a collection of convenient engineering tools and empirical manufacturing guidance to support the fabrication of the designed quad-robot. We validate the feasibility of designs generated with our system through physics simulations and with a physically-fabricated prototype

Computational design of planar multistable compliant structures

This paper presents a method for designing planar multistable compliant structures. Given a sequence of desired stable states and the corresponding poses of the structure, we identify the topology and geometric realization of a mechanism—consisting of bars and joints—that is able to physically reproduce the desired multistable behavior. In order to solve this problem efficiently, we build on insights from minimally rigid graph theory to identify simple but effective topologies for the mechanism. We then optimize its geometric parameters, such as joint positions and bar lengths, to obtain correct transitions between the given poses. Simultaneously, we ensure adequate stability of each pose based on an effective approximate error metric related to the elastic energy Hessian of the bars in the mechanism. As demonstrated by our results, we obtain functional multistable mechanisms of manageable complexity that can be fabricated using 3D printing. Further, we evaluated the effectiveness of our method on a large number of examples in the simulation and fabricated several physical prototypes

Modular Systems For Fabrication: Toward A Collaborative Partnership Between Humans and Machines

In recent decades, considerable advances have allowed more people to use digital fabrication techniques such as 3D Printing to create personal artifacts. Instead of collaborating with humans to create a design, current fabrication machines, however, mostly follow humans&rsquo; commands as one step input in order to output a physical object as a batch process. This way of working presents three big challenges: end-users without special knowledge can not fully appreciate advances of digital fabrication, machines cannot understand people&rsquo;s design activities during the creative process with improvisation, and fabrication machines are not designed to be collaborative to support individuals&rsquo; creative processes with in-situ designs. In this dissertation, I introduce the research to answer the overarching question: &ldquo;How can humans and machines form a collaborative partnership in a creative process?&rdquo; I investigate three elements and their influences at the intersections of HCI, digital fabrication, and collaborative systems to address these three main challenges. I present interactive design tools for end-users to design complex moveable objects(Fabrication-HCI), empirical studies to understand individuals&rsquo; design abilities and remaining challenges in developing collaborative fab machines (HCI-Collaborative Systems), and a collaborative 3D printer I built to enable close interactions between users and machines through multiple communication channels and various workflows (Fabrication-Collaborative Systems). I conclude my dissertation with a vision of an intelligent fabrication agent towards the future of people and machines augmenting each other. I propose new research programs for developing an intelligent machine that detects and predicts human behaviors in creative processes, in order to provide various types of assistance depending on the context, such as guidance, recommendation, and teaching new skills.</p