Patents by Inventor Matthew C. Putman

Matthew C. Putman 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).

  • Publication number: 20220284549
    Abstract: An inspection apparatus includes a specimen stage, one or more imaging devices and a set of lights, all controllable by a control system. By translating or rotating the one or more imaging devices or specimen stage, the inspection apparatus can capture a first image of the specimen that includes a first imaging artifact to a first side of a reference point and then capture a second image of the specimen that includes a second imaging artifact to a second side of the reference point. The first and second imaging artifacts can be cropped from the first image and the second image respectively, and the first image and the second image can be digitally stitched together to generate a composite image of the specimen that lacks the first and second imaging artifacts.
    Type: Application
    Filed: May 23, 2022
    Publication date: September 8, 2022
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, John B. Putman, John Moffitt, Michael Moskie, Jeffrey Andresen, Scott Pozzi-Loyola, Julie Orlando
  • Publication number: 20220276481
    Abstract: A method and system for mapping fluid objects on a substrate using a microscope inspection system that includes a light source, imaging device, stage for moving a substrate disposed on the stage, and a control module. A computer analysis system includes an object identification module that identifies for each of the objects on the substrate, an object position on the substrate including a set of X, Y, and ? coordinates using algorithms, networks, machines and systems including artificial intelligence and image processing algorithms. At least one of the objects is fluid and has shifted from a prior position or deformed from a prior size.
    Type: Application
    Filed: May 16, 2022
    Publication date: September 1, 2022
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, John B. Putman, John Cruickshank, Julie Orlando, Adele Frankel, Brandon Scott
  • Publication number: 20220269254
    Abstract: A computing system identifies a trajectory example generated by a human operator. The trajectory example includes trajectory information of the human operator while performing a task to be learned by a control system of the computing system. Based on the trajectory example, the computing system trains the control system to perform the task exemplified in the trajectory example. Training the control system includes generating an output trajectory of a robot performing the task. The computing system identifies an updated trajectory example generated by the human operator based on the trajectory example and the output trajectory of the robot performing the task. Based on the updated trajectory example, the computing system continues to train the control system to perform the task exemplified in the updated trajectory example.
    Type: Application
    Filed: February 25, 2022
    Publication date: August 25, 2022
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Andrew Sundstrom, Damas Limoge, Vadim Pinskiy, Aswin Raghav Nirmaleswaran, Eun-Sol Kim
  • Patent number: 11416711
    Abstract: A computing system generates a training data set for training the prediction model to detect defects present in a target surface of a target specimen and training the prediction model to detect defects present in the target surface of the target specimen based on the training data set. The computing system generates the training data set by identifying a set of images for training the prediction model, the set of images comprising a first subset of images. A deep learning network generates a second subset of images for subsequent labelling based on the set of images comprising the first subset of images. The deep learning network generates a third subset of images for labelling based on the set of images comprising the first subset of images and the labeled second subset of images. The computing system continues the process until a threshold number of labeled images is generated.
    Type: Grant
    Filed: March 9, 2021
    Date of Patent: August 16, 2022
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Tonislav Ivanov, Denis Babeshko, Vadim Pinskiy, Matthew C. Putman, Andrew Sundstrom
  • Patent number: 11408829
    Abstract: The disclosed technology relates to an inspection apparatus that includes a stage configured to retain a specimen for inspection, an imaging device having a field of view encompassing at least a portion of the stage to view a specimen retained on the stage, and a plurality of lights disposed on a moveable platform. The inspection apparatus can further include a control module coupled to the imaging device, each of the lights and the moveable platform. The control module is configured to perform operations including: receiving image data from the imaging device, where the image data indicates an illumination landscape of light incident on the specimen; and automatically modifying, based on the image data, an elevation of the moveable platform or an intensity of one or more of the lights to adjust the illumination landscape. Methods and machine-readable media are also contemplated.
    Type: Grant
    Filed: February 8, 2021
    Date of Patent: August 9, 2022
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, John B. Putman, John Moffitt, Michael Moskie, Jeffrey Andresen, Scott Pozzi-Loyola, Julie Orlando
  • Patent number: 11411293
    Abstract: A system is disclosed herein. The system includes a splitter board. The splitter board includes a microprocessor, a converter, and a bypass relay. The converter includes analog-to-digital circuitry and digital-to-analog circuitry. The bypass relay is configurable between a first state and a second state. In the first state, the bypass relay is configured to direct an input signal to the converter. The converter converts the input signal to a converted input signal and splits the converted input signal into a first portion and a second portion. The first portion is directed to the microprocessor. The second portion is directed to an output port of the splitter board for downstream processes. In the second state, the bypass relay is configured to cause the input signal to bypass the converter. The bypass relay directs the input signal to the output port of the splitter board for the downstream processes.
    Type: Grant
    Filed: December 28, 2021
    Date of Patent: August 9, 2022
    Assignee: Nanotronics Imaging, Inc.
    Inventors: John B. Putman, Matthew C. Putman, Damas Limoge, Michael Moskie, Jonathan Lee
  • Patent number: 11409367
    Abstract: An apparatus for manipulating an object includes first and second gesture controllers, each operatively connected to the object and structured and programmed such that, in a first-action active state, each can causes a first action to be carried out on the object by an appropriate first-action gesture made in the gesture controller. Only one of the first and second gesture controllers at any given time is capable of being in the first-action active state, and the first-action active state is transferable between the first and second gesture controllers upon the detecting of a first-action transfer gesture by one of said first gesture controller and said second gesture controller. Specific gesture control apparatus and methods for manipulating an object are also disclosed.
    Type: Grant
    Filed: January 22, 2021
    Date of Patent: August 9, 2022
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, John B. Putman, Paul Roossin
  • Publication number: 20220229267
    Abstract: An automatic focus system for an optical microscope that facilitates faster focusing by using at least two cameras. The first camera can be positioned in a first image forming conjugate plane and receives light from a first illumination source that transmits light in a first wavelength range. The second camera can be positioned at an offset distance from the first image forming conjugate plane and receives light from a second illumination source that transmits light in a second wavelength range.
    Type: Application
    Filed: April 4, 2022
    Publication date: July 21, 2022
    Applicant: Nanotronics Imaging, Inc.
    Inventors: John B. Putman, Matthew C. Putman, Julie Orlando, Dylan Fashbaugh
  • Publication number: 20220221703
    Abstract: A fluorescence microscopy inspection system includes light sources able to emit light that causes a specimen to fluoresce and light that does not cause a specimen to fluoresce. The emitted light is directed through one or more filters and objective channels towards a specimen. A ring of lights projects light at the specimen at an oblique angle through a darkfield channel. One of the filters may modify the light to match a predetermined bandgap energy associated with the specimen and another filter may filter wavelengths of light reflected from the specimen and to a camera. The camera may produce an image from the received light and specimen classification and feature analysis may be performed on the image.
    Type: Application
    Filed: April 4, 2022
    Publication date: July 14, 2022
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, John B. Putman, Vadim Pinskiy, Denis Sharoukhov
  • Patent number: 11341617
    Abstract: An inspection apparatus includes a specimen stage, one or more imaging devices and a set of lights, all controllable by a control system. By translating or rotating the one or more imaging devices or specimen stage, the inspection apparatus can capture a first image of the specimen that includes a first imaging artifact to a first side of a reference point and then capture a second image of the specimen that includes a second imaging artifact to a second side of the reference point. The first and second imaging artifacts can be cropped from the first image and the second image respectively, and the first image and the second image can be digitally stitched together to generate a composite image of the specimen that lacks the first and second imaging artifacts.
    Type: Grant
    Filed: February 8, 2021
    Date of Patent: May 24, 2022
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, John B. Putman, John Moffitt, Michael Moskie, Jeffrey Andresen, Scott Pozzi-Loyola, Julie Orlando
  • Patent number: 11333876
    Abstract: A method and system for mapping fluid objects on a substrate using a microscope inspection system that includes a light source, imaging device, stage for moving a substrate disposed on the stage, and a control module. A computer analysis system includes an object identification module that identifies for each of the objects on the substrate, an object position on the substrate including a set of X, Y, and ? coordinates using algorithms, networks, machines and systems including artificial intelligence and image processing algorithms. At least one of the objects is fluid and has shifted from a prior position or deformed from a prior size.
    Type: Grant
    Filed: October 8, 2020
    Date of Patent: May 17, 2022
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, John B. Putman, John Cruickshank, Julie Orlando, Adele Frankel, Brandon Scott
  • Publication number: 20220121169
    Abstract: Aspects of the disclosed technology provide a computational model that utilizes machine learning for detecting errors during a manual assembly process and determining a sequence of steps to complete the manual assembly process in order to mitigate the detected errors. In some implementations, the disclosed technology evaluates a target object at a step of an assembly process where an error is detected to a nominal object to obtain a comparison. Based on this comparison, a sequence of steps for completion of the assembly process of the target object is obtained. The assembly instructions for creating the target object are adjusted based on this sequence of steps.
    Type: Application
    Filed: December 27, 2021
    Publication date: April 21, 2022
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, Eun-Sol Kim, Andrew Sundstrom
  • Patent number: 11294162
    Abstract: A fluorescence microscopy inspection system includes light sources able to emit light that causes a specimen to fluoresce and light that does not cause a specimen to fluoresce. The emitted light is directed through one or more filters and objective channels towards a specimen. A ring of lights projects light at the specimen at an oblique angle through a darkfield channel. One of the filters may modify the light to match a predetermined bandgap energy associated with the specimen and another filter may filter wavelengths of light reflected from the specimen and to a camera. The camera may produce an image from the received light and specimen classification and feature analysis may be performed on the image.
    Type: Grant
    Filed: January 24, 2020
    Date of Patent: April 5, 2022
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, John B. Putman, Vadim Pinskiy, Denis Sharoukhov
  • Patent number: 11294146
    Abstract: An automatic focus system for an optical microscope that facilitates faster focusing by using at least two cameras. The first camera can be positioned in a first image forming conjugate plane and receives light from a first illumination source that transmits light in a first wavelength range. The second camera can be positioned at an offset distance from the first image forming conjugate plane and receives light from a second illumination source that transmits light in a second wavelength range.
    Type: Grant
    Filed: December 16, 2019
    Date of Patent: April 5, 2022
    Assignee: Nanotronics Imaging, Inc.
    Inventors: John B. Putman, Matthew C. Putman, Julie Orlando, Dylan Fashbaugh
  • Publication number: 20220043420
    Abstract: Aspects of the disclosed technology provide an Artificial Intelligence Process Control (AIPC) for automatically detecting errors in a manufacturing workflow of an assembly line process, and performing error mitigation through the update of instructions or guidance given to assembly operators at various stations. In some implementations, the disclosed technology utilizes one or more machine-learning models to perform error detection and/or propagate instructions/assembly modifications necessary to rectify detected errors or to improve the product of manufacture.
    Type: Application
    Filed: October 25, 2021
    Publication date: February 10, 2022
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, Eun-Sol Kim, Andrew Sundstrom
  • Publication number: 20220024140
    Abstract: Systems, methods, and media for additive manufacturing are provided. In some embodiments, an additive manufacturing system comprises: a hardware processor that is configured to: receive a captured image; apply a trained failure classifier to a low-resolution version of the captured image; determine that a non-recoverable failure is not present in the printed layer of the object; generate a cropped version of the low-resolution version of the captured image; apply a trained binary error classifier to the cropped version of the low-resolution version of the captured image; determine that an error is present in the printed layer of the object; apply a trained extrusion classifier to the captured image, wherein the trained extrusion classifier generates an extrusion quality score; and adjust a value of a parameter of the print head based on the extrusion quality score to print a subsequent layer of the printed object.
    Type: Application
    Filed: August 6, 2021
    Publication date: January 27, 2022
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Vadim Pinskiy, Matthew C. Putman, Damas Limoge, Aswin Raghav Nirmaleswaran
  • Patent number: 11209795
    Abstract: Aspects of the disclosed technology provide a computational model that utilizes machine learning for detecting errors during a manual assembly process and determining a sequence of steps to complete the manual assembly process in order to mitigate the detected errors. In some implementations, the disclosed technology evaluates a target object at a step of an assembly process where an error is detected to a nominal object to obtain a comparison. Based on this comparison, a sequence of steps for completion of the assembly process of the target object is obtained. The assembly instructions for creating the target object are adjusted based on this sequence of steps.
    Type: Grant
    Filed: April 20, 2020
    Date of Patent: December 28, 2021
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, Eun-Sol Kim, Andrew Sundstrom
  • Publication number: 20210394456
    Abstract: A manufacturing system is disclosed herein. The manufacturing system includes one or more stations, a monitoring platform, and a computing system. The computing system receives an image of the product at a step of the multi-step manufacturing process. The computing system determines a current state of the product based on the image of the product. The computing system determines, via a deep learning model, that the product is not within specification based on the current state of the product and the image of the product. Based on the determining, the computing system adjusts a control logic for at least a following station. The adjusting includes generating, by the deep learning model, a corrective action to be performed by the following station.
    Type: Application
    Filed: September 8, 2021
    Publication date: December 23, 2021
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Fabian Hough, John B. Putman, Matthew C. Putman, Vadim Pinskiy, Damas Limoge, Aswin Raghav Nirmaleswaran, Sadegh Nouri Gooshki
  • Publication number: 20210387421
    Abstract: Additive manufacturing systems using artificial intelligence can identify an anomaly in a printed layer of an object from a generated topographical image of the printed layer. The additive manufacturing systems can also use artificial intelligence to determine a correlation between the identified anomaly and one or more print parameters, and adaptively adjust one or more print parameters. The additive manufacturing systems can also use artificial intelligence to optimize one or more printing parameters to achieve desired mechanical, optical and/or electrical properties.
    Type: Application
    Filed: August 23, 2021
    Publication date: December 16, 2021
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, James Williams, III, Damas Limoge, Aswin Raghav Nirmaleswaran, Mario Chris
  • Publication number: 20210382990
    Abstract: A system including a deep learning processor receives one or more control signals from one or more of a factory's process, equipment and control (P/E/C) systems during a manufacturing process. The processor generates expected response data and expected behavioral pattern data for the control signals. The processor receives production response data from the one or more of the factory's P/E/C systems and generates production behavioral pattern data for the production response data. The process compares at least one of: the production response data to the expected response data, and the production behavioral pattern data to the expected behavioral pattern data to detect anomalous activity. As a result of detecting anomalous activity, the processor performs one or more operations to provide notice or cause one or more of the factory's P/E/C systems to address the anomalous activity.
    Type: Application
    Filed: August 23, 2021
    Publication date: December 9, 2021
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, John B. Putman, Vadim Pinskiy, Damas Limoge, Andrew Sundstrom, James Williams, III