Patents by Inventor Aswin Raghav Nirmaleswaran

Aswin Raghav Nirmaleswaran 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: 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
  • 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
  • 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
  • Patent number: 11117328
    Abstract: A manufacturing system is disclosed herein. The manufacturing system includes one or more stations, a monitoring platform, and a control module. Each station of the one or more stations is configured to perform at least one step in a multi-step manufacturing process for a product. The monitoring platform is configured to monitor progression of the product throughout the multi-step manufacturing process. The control module is configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the product.
    Type: Grant
    Filed: September 9, 2020
    Date of Patent: September 14, 2021
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Fabian Hough, John B. Putman, Matthew C. Putman, Vadim Pinskiy, Damas Limoge, Aswin Raghav Nirmaleswaran, Sadegh Nouri Gooshki
  • Publication number: 20210263495
    Abstract: A manufacturing system is disclosed herein. The manufacturing system includes one or more stations, a monitoring platform, and a control module. Each station of the one or more stations is configured to perform at least one step in a multi-step manufacturing process for a component. The monitoring platform is configured to monitor progression of the component throughout the multi-step manufacturing process. The control module is configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the component.
    Type: Application
    Filed: February 19, 2021
    Publication date: August 26, 2021
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, Damas Limoge, Sadegh Nouri Gooshki, Aswin Raghav Nirmaleswaran, Fabian Hough
  • Patent number: 11097490
    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: Grant
    Filed: December 20, 2019
    Date of Patent: August 24, 2021
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, James Williams, III, Damas Limoge, Aswin Raghav Nirmaleswaran, Mario Chris
  • Patent number: 11084225
    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: Grant
    Filed: April 20, 2020
    Date of Patent: August 10, 2021
    Assignee: NANOTRONICS IMAGING, INC.
    Inventors: Vadim Pinskiy, Matthew C. Putman, Damas Limoge, Aswin Raghav Nirmaleswaran
  • Publication number: 20210192779
    Abstract: A manufacturing system is disclosed herein. The manufacturing system includes one or more stations, a monitoring platform, and a control module. Each station of the one or more stations is configured to perform at least one step in a multi-step manufacturing process for a component. The monitoring platform is configured to monitor progression of the component throughout the multi-step manufacturing process. The control module is configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the component.
    Type: Application
    Filed: March 9, 2021
    Publication date: June 24, 2021
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, Andrew Sundstrom, Aswin Raghav Nirmaleswaran, Eun-Sol Kim
  • Publication number: 20210138735
    Abstract: A manufacturing system is disclosed herein. The manufacturing system may include one or more station, a monitoring platform, and a control module. Each station is configured to perform at least one step in a multi-step manufacturing process for a component. The monitoring platform is configured to monitor progression of the component throughout the multi-step manufacturing process. The control module is configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the component.
    Type: Application
    Filed: November 6, 2020
    Publication date: May 13, 2021
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Damas Limoge, Fabian Hough, Sadegh Nouri Gooshki, Aswin Raghav Nirmaleswaran, Vadim Pinskiy
  • Publication number: 20210069990
    Abstract: A manufacturing system is disclosed herein. The manufacturing system includes one or more stations, a monitoring platform, and a control module. Each station of the one or more stations is configured to perform at least one step in a multi-step manufacturing process for a product. The monitoring platform is configured to monitor progression of the product throughout the multi-step manufacturing process. The control module is configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the product.
    Type: Application
    Filed: September 9, 2020
    Publication date: March 11, 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: 20200247063
    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: April 20, 2020
    Publication date: August 6, 2020
    Inventors: Vadim Pinskiy, Matthew C. Putman, Damas Limoge, Aswin Raghav Nirmaleswaran
  • Publication number: 20200247061
    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: December 20, 2019
    Publication date: August 6, 2020
    Inventors: Matthew C. Putman, Vadim Pinskiy, James Williams, Damas Limoge, Aswin Raghav Nirmaleswaran, Mario Chris
  • Patent number: 10518480
    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: Grant
    Filed: April 2, 2018
    Date of Patent: December 31, 2019
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, James Williams, III, Damas Limoge, Aswin Raghav Nirmaleswaran, Mario Chris
  • Publication number: 20190299536
    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: April 2, 2018
    Publication date: October 3, 2019
    Inventors: Matthew C. Putman, Vadim Pinskiy, James Williams, III, Damas Limoge, Aswin Raghav Nirmaleswaran, Mario Chris