Disney Enterprises, Inc.

Eidgenossische Technische Hochschule Zurich

Moritz Niklaus Bächer

Lars Espen Knoop

Christian Gabriel Schumacher

Stelian Coros

Bernhard Thomaszewski

Lanny Starkes Smoot

Markus H Gross

Derek Edward Bradley

Thabo D Beeler

Bernd Bickel

Alfredo Medina Ayala

Günter D Niemeyer

Yeara Kozlov

Kyle Michael Cesare

Michael Anthony Hopkins

Vinay Chawda

Fabrizio Pece

Hongyi Xu

Tanner J Rinke

Otmar Hilliges

Matthew Keith Xi-Jie Pan

Sungjoon Choi

Paul Gregory Kry

Jonas Alois Zehnder

Venkata Krishna Tamminana

Benjamin Hepp

A new controller for use in robots with kinematic loops as well as in most other types of robots (such as those with fully actuated kinematic trees). The controller includes an inverse kinematics (IK) module that implements a versatile IK formulation for retargeting of motions, including expressive motions, onto mechanical systems (i.e., robots with loops and/or without loops). Further, the controller is configured to support the precise control of the position and orientation of end effectors and the center of mass (CoM) (such as of walking robots). The formulation of the algorithms carried out by the IK module safeguards against a disassembly when IK targets are moved outside the workspace of the robot. A regularizer is included in the controller that smoothly circumvents kinematic singularities where velocities go to infinity.

Robot with an inverse kinematics (IK)-based controller for retargeting input motions

A robot control method, and associated robot controllers and robots operating with such methods and controllers, providing real-time vibration suppression. The control method involves learning to support real-time, vibration-suppressing control. The method uses state-of-the-art machine learning techniques in conjunction with a differentiable dynamics simulator to yield fast and accurate vibration suppression. Vibration suppression using offline simulation approaches that can be computationally expensive may be used to create training data for the controller, which may be provide by a variety of neural network configurations. In other cases, sensory feedback from sensors onboard the robot being controlled can be used to provide training data to account for wear of the robot's components.

Robotic systems using learning to provide real-time vibration-suppressing control

Methods and corresponding systems that are useful in design and fabrication of kinetic wire mechanisms or characters. The method includes a computational technique for the design of kinetic wire mechanisms tailored for fabrication on consumer-grade hardware such as a desktop CNC bending device. The method takes as input a skeletal animation of the mechanism to be fabricated and estimates, from the skeletal animation, a cable-driven and compliant wire structure, which matches user-selected keyframes. To enable localized deformations, the technique involves shaping the mechanism's body (i.e., the wire) into functional spring-like entities at a set of locations along the length of the mechanism's body. The method involves determining where on the wire body to place these spring-like entities, determining which types or configurations of spring-like entities should be placed at each of these locations, and optimizing parameters of each user-selected spring-like entity for use at the locations on the wire mechanism.

Computer-assisted design and fabrication of kinetic wire mechanisms

A 3D printer system with a structural optimization tool to generate 3D models optimized for build materials such as those used in binder jetting technology-based printers. The structural optimization tool uses a computational approach to optimize mechanical and mass properties of large-scale structures (i.e., objects to be 3D printed), and the computational approach is tailored for fabrication on binder jetting technologies. To spend a material budget for printing an object wisely, the inventors in designing the computational approach turned the Bresler-Pister failure criterion into an objective measuring the potential of failure of an object or structure. This involved modeling the difference in tensile and compressive strength of the build material. To optimize structures under worst-case loads, the computational approach unifies an optimization to identify worst-case loads with an optimization to minimize the resulting failure potential, nesting them with first-order optimality constraints.

Optimizing 3D printed large-scale structures under worst-case loads

A system for providing a user of a virtual reality (VR) system with physical interactions with an object in the real world or in the surrounding physical space while they are concurrently interacting in the virtual world with a corresponding virtual object. The real world object is dynamic with the system including a physical interaction system that includes a robot with a manipulator for moving, positioning, and/or orienting the real world object to move it into contact with the user. For example, the physical object is moved into contact with a tracked body part of the user at a time that is synchronized with a time of an interaction event occurring in the virtual world being created by the VR system. Further, a system is described for providing a dynamic physical interaction to a human participant, e.g., a fast and compelling handover in an augmented reality (AR) system.

System for introducing physical experiences into virtual reality (VR) worlds

Embodiments herein describe deformable controllers that rely on piezoelectric material embedded in the controllers to detect when the input device is being manipulated into a particular deformation or gesture. The computing system may perform different actions depending on which deformation is detected. The embodiments herein describe design techniques for optimizing the placement of the piezoelectric material in the controller to improve the accuracy of a mapping function that maps sensor responses of the material to different controller deformations. In one embodiment, the user specifies the different deformations of the controller she wishes to be recognized by the computing system (e.g., raising a leg, twisting a torso, squeezing a hand, etc.). The design optimizer uses the locations of the desired deformations to move the location of the piezoelectric material such that the sensor response of the material can be uniquely mapped to these locations.

Designing customized deformable input devices using simulated piezoelectric sensor responses

Methods, systems, and computer-readable memory are provided for determining time-varying anatomical and physiological tissue characteristics of an animation rig. For example, shape and material properties are defined for a plurality of sample configurations of the animation rig. The shape and material properties are associated with the plurality of sample configurations. An animation of the animation rig is obtained, and one or more configurations of the animation rig are determined for one or more frames of the animation. The determined one or more configurations include shape and material properties, and are determined using one or more sample configurations of the animation rig. A simulation of the animation rig is performed using the determined one or more configurations. Performing the simulation includes computing physical effects for addition to the animation of the animation rig.

Methods and systems of enriching blendshape rigs with physical simulation

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Zurich, Switzerland

Moritz Niklaus Bächer