Patents by Inventor Christian Gabriel SCHUMACHER
Christian Gabriel SCHUMACHER has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240399579Abstract: A system for designing a robotic device, includes a processor configured to: receive a target animation for a character to be represented by the robotic device; receive an initial model of the robotic device, the model including a plurality of configurable joints and a plurality of actuators; generate a kinematic design of the robotic device based on the initial model and the target animation; generate control parameters for the plurality of actuators based on the kinematic design; generate a physical design for the robotic device based on the kinematic design and the control parameters; and deploy the physical design to the robotic device.Type: ApplicationFiled: May 21, 2024Publication date: December 5, 2024Inventors: Moritz Niklaus Bächer, Christian Gabriel Schumacher, Lars Espen Knoop, Guirec G.H.F. Maloisel, Ruben Jelle Grandia
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Publication number: 20240269899Abstract: A computer-assisted method (and a computer system implementing a design tool and skin fabricated according to these designs) for designing elastomeric skin for robots and robotic devices. The skin design tool is configured to facilitate the optimal navigation of the design space spanned by an animatronic or robotic device skin. The skin design tool includes a soft body simulator that is differentiable with respect to control and design parameters, which enables the skin design tool to provide one or more of the following applications: (1) automated identification of an optimal neutral pose for the skin that minimizes peak stresses when the skin is brought into extreme poses; (2) automated optimization of the skin thickness and shape of a skin to meet a time-varying artistic target; and (3) automated optimization of a skin to achieve a desired behavior if the skin is allowed to slide along an underlying rigid shell.Type: ApplicationFiled: February 15, 2023Publication date: August 15, 2024Inventors: Moritz Niklaus Bächer, Daniele Panozzo, Denis Zorin, Arvi Gjoka, Lars Espen Knoop, Christian Gabriel Schumacher
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Publication number: 20240248491Abstract: Techniques for generating robotics control signals are disclosed. Movement data is received for a desired motion for a robotics device, which can include animation, motion capture, sensor data, or movement of a different robotics device. Robotics device data is received, including control data and reference points corresponding to locations on the robotics device. A correlation is determined between movement data points in the movement data and the reference points. Using the control data, a control signal is determined based on the desired motion. The control signal is based on a distance between at least one movement data point and at least one reference point. The disclosed technology can retarget motions onto under-actuated systems and without regard to differences in degrees of freedom, mass distributions, and proportions of robotics devices.Type: ApplicationFiled: December 22, 2023Publication date: July 25, 2024Inventors: Moritz Niklaus Bächer, Farbod Farshidian, Marco Hutter, Ruben Jelle Grandia, Lars Espen Knoop, Christian Gabriel Schumacher
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Publication number: 20240227173Abstract: An automated design method, and corresponding computer system for implementing such a method and robot mechanism with an optimized flexible link, that is configured to optimize a desired load-displacement behavior of planar flexible-link mechanisms at expected points of interaction. To implement the new design method, a subset of rigid links of an existing rigid-link robot mechanism are replaced with flexible links, optimizing their rest configurations. The efficacy of the design approach has been proven with two fabricated prototypes of robot mechanisms, with one being adapted for grasping tasks and one being adapted for locomotion tasks.Type: ApplicationFiled: January 5, 2023Publication date: July 11, 2024Inventors: Moritz Niklaus Bächer, Christian Gabriel Schumacher, Bernhard Steffen Thomaszewski, Lars Espen Knoop, Stelian Coros, Guirec G.H.F. Maloisel
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Publication number: 20240051124Abstract: Systems and methods for training a neural network to predict states of a robotics device are disclosed. Robotics data is received for a robotics device, including indications of a set of components, a digital simulation of the robotics device, and measurement data received from a sensor associated with the robotics device. The set of components includes an actuator and a structural element. A training dataset is generated using the received robotics data. Generating the training dataset includes comparing the measurement data with simulated measurement data based on the digital simulation. A neural network is trained using the generated training dataset to modify the digital simulation of the robotics device to predict a state of the robotics device, such as a position, motion, electrical quantity, or other. When trained, the neural network is applied to predict states of the robotics device or a different robotics device.Type: ApplicationFiled: August 9, 2023Publication date: February 15, 2024Inventors: Moritz Niklaus Bacher, Christian Gabriel Schumacher, Komath Naveen Kumar, Lars Espen Knoop, Agon Serifi
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Patent number: 11787045Abstract: 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.Type: GrantFiled: April 6, 2021Date of Patent: October 17, 2023Assignee: Disney Enterprises, Inc.Inventors: Moritz Niklaus Bacher, Lars Espen Knoop, Michael Anthony Hopkins, Kyle Michael Cesare, Christian Gabriel Schumacher, Stelian Coros
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Publication number: 20230286144Abstract: In one example, a robotic system is disclosed that includes a plurality of components coupled together, a plurality of motors operable to move the plurality of components, a controller in electrical communication with the plurality of motors to generate control signals to actuate movement of the plurality of components, wherein the controller is configured to: receive a first set of control signals operative to generate a defined motion for the plurality of components, analyze the first set of control signals to determine a second set of control signals operative to define a retargeted motion for the plurality of components, wherein the retargeted motion suppresses vibrations of the plurality of components as compared to the defined motion, and provide the second set of control signals to the plurality of motors to actuate the retargeted motion by the plurality of components.Type: ApplicationFiled: May 22, 2023Publication date: September 14, 2023Inventors: Tanner Rinke, Venkata Krishna Tamminana, Alfredo Medina Ayala, Sungjoon Choi, Moritz Niklaus Bacher, Lars Espen Knoop, Christian Gabriel Schumacher
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Patent number: 11701774Abstract: 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.Type: GrantFiled: December 16, 2020Date of Patent: July 18, 2023Assignee: Disney Enterprises, Inc.Inventors: Tanner Rinke, Venkata Krishna Tamminana, Alfredo Medina Ayala, Sungjoon Choi, Moritz Niklaus Bacher, Lars Espen Knoop, Christian Gabriel Schumacher
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Publication number: 20220226987Abstract: 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.Type: ApplicationFiled: April 6, 2021Publication date: July 21, 2022Inventors: Moritz Niklaus Bacher, Lars Espen Knoop, Michael Anthony Hopkins, Kyle Michael Cesare, Christian Gabriel Schumacher, Stelian Coros
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Publication number: 20220184802Abstract: 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.Type: ApplicationFiled: December 16, 2020Publication date: June 16, 2022Inventors: Tanner Rinke, Venkata Krishna Tamminana, Alfredo Medina Ayala, Sungjoon Choi, Moritz Niklaus Bacher, Lars Espen Knoop, Christian Gabriel Schumacher
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Publication number: 20220134552Abstract: A system providing dynamic balancing in a robotic system. The system includes memory storing a definition of a robot and storing an input animation for the robot specifying motion of components of the robot. A simulator performs a dynamic simulation of the robot performing the input animation including modeling a first set of the components as flexible components and a second set of the components as rigid components. Each of the flexible components is coupled at opposite ends to one of the rigid components. An optimizer generates a retargeted motion for the components to provide dynamic balancing of the robot performing the retargeted motion. The optimizer generates the retargeted motion by transforming forces acting on the robot to a local contact frame rigidly moving with the robot. The optimizer generates the retargeted motion so a zero-moment point of the robot lies in a support area of the robot's feet.Type: ApplicationFiled: January 12, 2022Publication date: May 5, 2022Inventors: Moritz Niklaus Bächer, Lars Espen Knoop, Christian Gabriel Schumacher
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Publication number: 20210232735Abstract: A system for performing simulation-based material characterization includes a computing platform having a hardware processor and a system memory storing a software code. The hardware processor executes the software code to obtain a result of a physical test performed on a material, selects a parameterized model of the material based on the obtained result, and performs a simulation of the physical test using the parameterized model to generate a simulated result. The hardware processor further executes the software code to compare the simulated result with the obtained result of the physical test on the material, and adjusts one or more parameter value(s) of the parameterized model, based on the comparison, to improve the simulated result, and predict, after adjusting the parameter value(s), one or more characteristics of the material based on the parameterized model.Type: ApplicationFiled: January 29, 2020Publication date: July 29, 2021Inventors: Moritz Niklaus Bächer, Gabriela Natalia Venturini, Christian Gabriel Schumacher, Cynthia A. Marinaro, Alfredo Ayala, Lars Espen Knoop, Philip J. Jackson
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Publication number: 20210141869Abstract: An automated mechanical design analysis system includes a computing platform having a hardware processor and a system memory storing a software code. The hardware processor executes the software code to receive an input model of a mechanical object, identify one or more design parameter(s) of the input model for automated analysis, and perform a parametric mapping of the input model based on the design parameter(s) to produce a parameterized model corresponding to the input model. The hardware processor further executes the software code to embed the parameterized model in a grid to produce model-grid intersections defining multiple subvolumes of the parameterized model, and generate a simulation of the input model based on the model-grid intersections and the subvolumes, where the simulation of the input model provides a differentiable mathematical representation of the input model.Type: ApplicationFiled: November 8, 2019Publication date: May 13, 2021Inventors: Moritz Niklaus Bächer, Christian Hafner, Bernd Bickel, Christian Gabriel Schumacher, Lars Espen Knoop
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Patent number: 10933623Abstract: 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.Type: GrantFiled: September 20, 2018Date of Patent: March 2, 2021Assignee: Disney Enterprises, Inc.Inventors: Moritz Niklaus Bächer, Christian Gabriel Schumacher, Jonas Alois Zehnder
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Publication number: 20190366703Abstract: 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.Type: ApplicationFiled: September 20, 2018Publication date: December 5, 2019Inventors: Moritz Niklaus BÄCHER, Christian Gabriel SCHUMACHER, Jonas Alois ZEHNDER