Disney Enterprises, Inc.

Inkbit, LLC

Mitsubishi Electric Research Laboratories, Inc.

Massachusetts Institute of Technology

Adobe, Inc.

Toyota Research Institute, Inc.

Other

Eth Zurich (eidgenossische Technische Hochschule Zurich)

Mitsubishi Electric Research Labs.

Eth Zurich (eidgenoessische Technische Hochschule Zurich)

Basf Se Corporation

Qatar Foundation for Education, Science and Community Development

Mitsubishi Electric Corporation

Wojciech Matusik

Desai Chen

Hanspeter Pfister

Javier E Ramos

Aaron Weber

Markus H Gross

Bernd Bickel

Gregory Ellson

Simon Heinzle

William T Freeman

Sylvain Philippe Paris

Shmuel Avidan

Frederic Durand

Alexander Sorkine Hornung

Philip John Jackson

Wojciech Jarosz

Ilya Baran

Bernhard Thomaszewski

Mohamed Hefeeda

Marios Papas

Matthias Zwicker

Anthony Vetro

Kalyan Krishna Sunkavalli

Sehoon Yea

Derek Edward Bradley

Thabo D Beeler

Paul A Beardsley

Simon A I Stent

Daniel Vlasic

Peter Charles Barnum

Fredo Durand

Michael Holroyd

Szu-Po Wang

Lanny Starkes Smoot

Oliver Wang

Paris Smaragdis

Quinn Smithwick

William Yerazunis

Daniela Rus

Neel Suresh Joshi

Markus Gross

Ce Liu

Jeroen Van Baar

Pitchaya Sitthi-Amorn

Harrison Wang

Kiril Vidimce

Marc Alexa

Petr Kellnhofer

Antonio Torralba

Jan Kautz

Szymon Marek Rusinkiewicz

Leonard McMillan, Jr

Wai Kit Addy Ngan

Wenshou Wang

Nicola V Ranieri

Piotr Krzysztof Didyk

Davide Marini

Yuwang Wang

Adrià Recasens

Ari Peter Berman

Changil Kim

Morgan S McGuire

Miguel A Otaduy

Yan Zhang

Stephen Robert Marschner

Peter Kaufmann

Tim A Weyrich

Christian Regg

Wan Shou

Mohamed Abdelaziz A Mohamed Elgharib

Wenzel A Jakob

Olivier Roullier

Michael J Foshey

Piotr K Didyk

Jinwei Gu

Jason Davis Lawrence

Kiana Ali Asghar Calagari

Remo Ziegler

Piotr Didyk

Alexandre Kaspar

Allen S Park

Tomas Apostol Palacios

Stelian Coros

Aljoscha Smolic

Klaus H Stoll

Aljosa Aleksej Andrej Smolic

Daniel James Reetz

Manuel Lang

Walter Henry Zengerle, Iii

Giovanni Vannucci

Bo Zhu

Bernhard Ulrich Von Vacano

Pierre Greisen

Steve Marschner

Simon Stent

Linjie Luo

Paul E Green

John F Hughes

Tim Weyrich

An approach to improving optical scanning increases the strength of optical reflection from the build material during fabrication. In some examples, the approach makes use of an additive (or a combination of multiple additives) that increases the received signal strength and/or improves the received signal-to-noise ratio in optical scanning for industrial metrology. Elements not naturally present in the material are introduced in the additives in order to increase fluorescence, scattering or luminescence. Such additives may include one or more of: small molecules, polymers, peptides, proteins, metal or semiconductive nanoparticles, and silicate nanoparticles.

Optical scanning for industrial metrology

Systems and methods are provided for estimating 3D poses of a subject based on tactile interactions with the ground. Test subject interactions with the ground are recorded using a sensor system along with reference information (e.g., synchronized video information) for use in correlating tactile information with specific 3D poses, e.g., by training a neural network based on the reference information. Then, tactile information received in response to a given subject interacting with the ground can be used to estimate the 3D pose of the given subject directly, i.e., without reference to corresponding reference information. Certain exemplary embodiments use a sensor system in the form of a pressure sensing carpet or mat, although other types of sensor systems using pressure or other sensors can be used in various alternative embodiments.

Systems and methods for estimating 3D position and movement from tactile signals

A method includes generating correction data for a construction material that is used by an additive-manufacturing machine to manufacture an object. This correction data compensates for an interaction of the construction material with first radiation that has been used to illuminate the construction material.

Reflective coating for material calibration

A method comprises using a three-dimensional additive manufacturing process to produce an interlocking volume, wherein using the additive manufacturing process includes depositing successive layers, each of which includes a first material distributed according to a first interlocking material pattern and a second material distributed according to a second interlocking material pattern, said second material differing from said first material.

Material interlocking

An approach to precision additive fabrication uses jetting of cationic compositions in conjunction with a non-contact (e.g., optical) feedback approach. By not requiring contact to control the surface geometry of the object being manufactured, the approach is tolerant of the relative slow curing of the cationic composition, while maintaining the benefit of control of the deposition processes according to feedback during the fabrication processes. This approach provides a way to manufacture precision objects and benefit from material properties of the fabricated objects, for example, with isotropic properties, which may be at least partially a result of the slow curing, and flexible structures, which may not be attainable using conventional jetted acrylates.

Precision system for additive fabrication

Arrangement of the parts, particularly addressing arrangement for 3D fabrication, makes use of spatial frequency domain representations of the parts, such that acceptable (or optionally desirable) relative locations (and optionally orientations) of a part relative to another part or an arrangement of multiple other parts makes use of spatial frequency domain representations of the parts. In some examples, acceptable relative locations may be defined as relative locations that do not result in parts spatially overlapping and/or maintain a desired (e.g., minimum, average, etc.) separation between parts.

Frequency domain spatial packing for 3D fabrication

An additive fabrication approach involves fabricating a platform on a build plate. The fabrication system is then calibrated based on the fabricated platform, and an object is then fabricating on the fabricated platform according to the calibration.

Calibration for additive manufacturing

Systems and methods for optimizing the formulation of materials are provided. The systems and methods employ a data-driven, iterative approach to derivate optimal material formulations. One portion of the system includes a sample automation system that outputs the material samples to be tested, and a second portion of the system includes an optimization engine that analyzes data extracted from the material samples and generates additional formulations for materials to be printed and tested. This process continues so that optimal material formulations can be determined based on desired mechanical properties of the material to be optimized. The optimization engine can further be capable of predicting results of formulation that have not yet been tested and using those predictions to further drive the next suggested materials to be tested.

Systems and methods for formulating material in a data-driven manner

A method for additive manufacturing includes forming an object including depositing a first material including a first coloring component and a second material including a second coloring component, wherein both the first material and the second material further include a corresponding fluorescent component, scanning the object, including causing an emission of an optical signal from the object, wherein the emission of the optical signal is caused at least in part by an emission from the fluorescent components interacting with the first coloring component and the second coloring component as it passes from the fluorescent components to the surface of the object, sensing the emission of the optical signal, and determining presence of the first material and the second material based at least in part on the sensed emission of the optical signal.

A profilometer provides, to a controller, a feedback signal indicative of topography of an exposed surface of an object that is being manufactured by a 3d printer. The profilometer includes an emitter and a camera. The emitter illuminates a region of surface of the object with a pattern having an edge that defines a boundary of an illuminated portion of the surface. The camera receives an image that transitions between a first state in which the edge is visible in the image at a location that is indicative of the surface's depth and a second state in which the edge is not visible at all. From this second state, the controller obtains information representative of a depth of the surface.

Edge profilometer

A wearable article comprising a knitted fabric formed in the shape of a glove. A force sensing element coupled to the fabric, the force sensing element comprising a resistive sensing system and a fluidic sensing system comprising one or more soft tubes coupled to a surface of the wearable glove wherein the resistive and fluid sensing systems correspond to first and second different sensor modalities which are physically decoupled. Control circuitry is coupled to receive signals from both the resistive sensing system and the fluidic sensing system and to combine resistive and fluidic sensing system signals provided thereto to perform at least one of: pose estimation, environment sensing, human state sensing, and static and dynamic task identification.

Wearable glove with hybrid resistive-pressure sensors

A method for additive fabrication by 3D printing includes processing model data representing material transition boundaries of an object to be printed to form build data for use in controlling printing of a plurality of successive layers to form the object, the build data comprising, for each location of a plurality of locations in a two-dimensional arrangement, material transition data for representing heights of material transitions in a third dimension, and repeating for each layer of the plurality of successive layers, receiving surface height data representing a height of a partial fabrication of the object at respective locations of a plurality of locations on a surface of the partial fabrication for each location of the plurality of locations, using the height at the location to access the material transition data corresponding to the location in the build data, and using the material transition data to determine material to be deposited at that location, and causing emission of the determined material at each location of the plurality of locations, thereby causing printing of the layer.

Object model encoding for additive fabrication

A method for managing the temperature of three-dimensional object during additive manufacturing includes depositing material on a partial fabrication of the three-dimensional object, determining thermal properties of the three-dimensional object after depositing the material, and controlling cooling of the object according to said thermal properties. In some examples, the determining of the thermal properties includes determining a temperature variation across the object and controlling position-dependent cooling of the object in a feedback arrangement. Resulting uniform temperature of the object under fabrication can improve dimensional accuracy and material properties of the object.

Thermal management for additive fabrication

A method includes receiving, with a computing device, an image, identifying one or more salient features in the image, and generating a saliency map of the image including the one or more salient features. The method further includes sampling the image based on the saliency map such that the one or more salient features are sampled at a first density of sampling and at least one portion of the image other than the one or more salient features are sampled at a second density of sampling, where the first density of sampling is greater than the second density of sampling, and storing the sampled image in a non-transitory computer readable memory.

Systems and methods for saliency-based sampling layer for neural networks

A manufacturing method includes using an additive manufacturing process to form a first object. The first object includes layers, among which is a first layer that comprises a first material and a second material. The first material surrounds the second material within the first layer. Both materials are solids that transition into liquids at corresponding first and second temperatures, the first temperature being lower than the second temperature. The method includes, after having formed the first object, exposing the first object to a temperature that is between the first temperature and the second temperature such that the first material melts, thereby leaving behind a second object, the second object comprising the second material.

Hybrid additive manufacturing with dual phase change materials

Growing community of inventors

Lexington, MA, United States of America

Wojciech Matusik