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.
@cite_23 proposed a process for designing synthetic skin and actuation parameters for animatronic characters that mimic facial expressions of a given subject. @cite_42 optimized the internal material distribution so that the resulting character exhibits the desired deformation behavior. Focusing on actuation, @cite_54 computed the layout of winch-tendon networks to animate plush toys, and @cite_78 optimized the chamber structure and material distribution for designing soft pneumatic objects.
@cite_54 @cite_42 @cite_78 @cite_23
2738703359 1983512267 2770227623 1990940174
We present a computational approach to creating animated plushies, soft robotic plush toys specifically-designed to reenact user-authored motions. Our design process is inspired by muscular hydrostat structures, which drive highly versatile motions in many biological systems. We begin by instrumenting simulated plush toys with a large number of small, independently-actuated, virtual muscle-fibers. Through an intuitive posing interface, users then begin animating their plushie. A novel numerical solver, reminiscent of inverse-kinematics, computes optimal contractions for each muscle-fiber such that the soft body of the plushie deforms to best match user input. By analyzing the co-activation patterns of the fibers that contribute most to the plushie's motions, our design system generates physically-realizable winch-tendon networks. Winch-tendon networks model the motorized cable-driven actuation mechanisms that drive the motions of our real-life plush toy prototypes. We demonstrate the effectiveness of our computational approach by co-designing motions and actuation systems for a variety of physically-simulated and fabricated plushies. We 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. We present an end-to-end solution for design and fabrication of soft pneumatic objects with desired deformations. Given a 3D object with its rest and deformed target shapes, our method automatically optimizes the chamber structure and material distribution inside the object volume so that the fabricated object can deform to all the target deformed poses with controlled air injection. To this end, our method models the object volume with a set of chambers separated by material shells. Each chamber has individual channels connected to the object surface and thus can be separately controlled with a pneumatic system, while the shell is comprised of base material with an embedded frame structure. A two-step algorithm is developed to compute the geometric layout of the chambers and frame structure as well as the material properties of the frame structure from the input. The design results can be fabricated with 3D printing and deformed by a controlled pneumatic system. We validate and demonstrate the efficacy of our method with soft pneumatic objects that have different shapes and deformation behaviors. We propose a complete process for designing, simulating, and fabricating synthetic skin for an animatronics character that mimics the face of a given subject and its expressions. The process starts with measuring the elastic properties of a material used to manufacture synthetic soft tissue. Given these measurements we use physics-based simulation to predict the behavior of a face when it is driven by the underlying robotic actuation. Next, we capture 3D facial expressions for a given target subject. As the key component of our process, we present a novel optimization scheme that determines the shape of the synthetic skin as well as the actuation parameters that provide the best match to the target expressions. We demonstrate this computational skin design by physically cloning a real human face onto an animatronics figure.