Patents by Inventor Sol Kim

Sol Kim 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: 20250147499
    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: November 25, 2024
    Publication date: May 8, 2025
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Andrew Sundstrom, Damas Limoge, Vadim Pinskiy, Aswin Raghav Nirmaleswaran, Eun-Sol Kim
  • Publication number: 20250135863
    Abstract: An electric vehicle body can be configured to minimize the entry of foreign matters in a replaceable battery pack region while facilitating battery pack replacement. An electric vehicle body can include first and second battery packs replaceably mounted on a chassis frame, a cover bracket extending on one side of the first battery pack, and an undercover extending on one side of the second battery pack adjacent to the first battery pack and overlapping the cover bracket to seal off a gap between the first battery pack and the second battery pack.
    Type: Application
    Filed: March 19, 2024
    Publication date: May 1, 2025
    Inventors: Gyung Hoon Shin, Chan Sol Kim, Jong Gyu Park
  • Publication number: 20250139798
    Abstract: The present disclosure relates to an apparatus for training and causing autonomous driving control of a vehicle. The apparatus may comprise at least one processor, and a memory storing instructions, when executed by the at least one processor, cause the apparatus to obtain, based on a depth map obtained from a cluster of points at a target time point, a depth distribution map, obtain, based on an input image that is associated with the target time point and that is applied to a monocular depth estimation (MDE) model, a depth estimation map, update, based on a loss function group applied to the MDE model, a plurality of weights included in the MDE model, wherein the loss function group may comprise a first loss function that is obtained based on the depth distribution map and the depth estimation map, and output a signal indicating the updated plurality of weights.
    Type: Application
    Filed: March 27, 2024
    Publication date: May 1, 2025
    Inventors: Jin Sol Kim, Jin Ho Park, Jang Yoon Kim
  • Publication number: 20250129489
    Abstract: Proposed are a flow-through reactor for conversion of carbon dioxide and a method for conversion of carbon dioxide using the flow-through reactor. Carbon dioxide and a catholyte are separately supplied, and a reference electrode having a large volume is capable of being mounted on an electrolyte pocket without increasing resistance since a structure of the electrolyte pocket is improved.
    Type: Application
    Filed: January 18, 2024
    Publication date: April 24, 2025
    Inventors: Da-Hye WON, Hyung-Suk OH, Ung LEE, Woong-Hee LEE, Dong-Ki LEE, Jai-Hyun KOH, Byoung-Koun MIN, Chan-Sol KIM, Dong-Jin KIM
  • Publication number: 20250104274
    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: December 9, 2024
    Publication date: March 27, 2025
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, Andrew Sundstrom, Aswin Raghav Nirmaleswaran, Eun-Sol Kim
  • Publication number: 20250095174
    Abstract: A learning device, a learning method thereof, a test device using the same, and a test method using the same are provided. The learning device may obtain a target image and a source image, generate an estimated depth map based on the target image via a first network, generate pose change information corresponding to a pose change between the target image and the source image, generate a composite image corresponding to the target image, determine a first loss based on the composite image and the target image, and determine a second loss, and back-propagate the first loss and the second loss and update a parameter of the first network and a parameter of the second network.
    Type: Application
    Filed: May 8, 2024
    Publication date: March 20, 2025
    Inventors: Jin Ho Park, Jin Sol Kim, Jang Yoon Kim
  • Publication number: 20250093853
    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: November 25, 2024
    Publication date: March 20, 2025
    Applicant: Nanotronics Imaging, Inc.
    Inventors: Andrew Sundstrom, Damas Limoge, Eun-Sol Kim, Vadim Pinskiy, Matthew C. Putman
  • Publication number: 20250078235
    Abstract: A learning device is introduced. The device may comprise a processor, and memory storing instructions that, when executed by the processor, may cause the device to obtain at least one first depth map based on at least one piece of cloud data associated with surrounding environment information, and at least one first image associated with the at least one first depth map, determine, based on the at least one first depth map and the at least one first image, variance estimation information indicating a variance between the at least one first depth map and the at least one first image, back-propagate a variance loss based on the first variance estimation information, and variance ground truth (GT) information associated with the first variance estimation information, and update, based on the back-propagated variance loss, a parameter associated with determining the first variance estimation information.
    Type: Application
    Filed: February 2, 2024
    Publication date: March 6, 2025
    Inventors: Jang Yoon Kim, Jin Sol Kim, Jin Ho Park
  • Publication number: 20250011583
    Abstract: The present disclosure relates to a thermoplastic resin composition, including 35 to 65% by weight of a polyamide resin (A); 18 to 40% by weight of glass fiber (B); 10 to 30% by weight of a composite flame retardant (C); 0.06 to 0.4% by weight of a phosphite-based thermal stabilizer (D); and 0.1 to 0.7% by weight of a copper-based composite thermal stabilizer (E), a method of preparing the thermoplastic resin composition, and a molded article including the thermoplastic resin composition.
    Type: Application
    Filed: January 5, 2023
    Publication date: January 9, 2025
    Inventors: Han Sol KIM, In Seok SEO, Jae Chan PARK
  • Publication number: 20250014198
    Abstract: An apparatus for estimating a depth is introduced. The apparatus may comprise a camera configured to capture an image may comprise an object, and a processor configured to perform, based on a deep learning model, a deep learning process associated with the image, obtain, based on the deep learning process associated with the image, a first depth value, obtain a partial image by masking a partial region of the image, perform, based on the deep learning model, a deep learning process associated with the partial image, obtain, based on the deep learning process associated with the partial image, a second depth value, train the deep learning model to reduce a deviation between the first depth value and the second depth value, and estimate, based on the trained deep learning model, a depth of the object.
    Type: Application
    Filed: November 30, 2023
    Publication date: January 9, 2025
    Inventors: Jin Ho Park, Jin Sol Kim, Jang Yoon Kim, Seung Ryong Kim, Jong Beom Baek, Seong Hoon Park, Gyeong Nyeon Kim
  • Patent number: 12165353
    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: Grant
    Filed: March 9, 2021
    Date of Patent: December 10, 2024
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, Andrew Sundstrom, Aswin Raghav Nirmaleswaran, Eun-Sol Kim
  • Patent number: 12153414
    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: Grant
    Filed: February 25, 2022
    Date of Patent: November 26, 2024
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Andrew Sundstrom, Damas Limoge, Vadim Pinskiy, Aswin Raghav Nirmaleswaran, Eun-Sol Kim
  • Patent number: 12153401
    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: Grant
    Filed: November 6, 2020
    Date of Patent: November 26, 2024
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Andrew Sundstrom, Damas Limoge, Eun-Sol Kim, Vadim Pinskiy, Matthew C. Putman
  • Patent number: 12153408
    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: Grant
    Filed: June 18, 2021
    Date of Patent: November 26, 2024
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Andrew Sundstrom, Eun-Sol Kim, Damas Limoge, Vadim Pinskiy, Matthew C. Putman
  • Publication number: 20240386686
    Abstract: The method for performing endoscopic examination according to an exemplary embodiment of the present invention may include the steps of obtaining an endoscopic image and a 3D model of a target organ; identifying location information of an endoscope on the 3D model in real time based on simultaneous localization and mapping (SLAM); classifying a plurality of areas constituting the 3D model into examination areas and unexamined areas by using the endoscopic image and the location information; and providing feedback information based on the examination areas and unexamined areas.
    Type: Application
    Filed: April 23, 2024
    Publication date: November 21, 2024
    Applicant: THE CATHOLIC UNIVERSITY OF KOREA INDUSTRY-ACADEMIC COOPERATION FOUNDATION
    Inventors: Bo-in LEE, Youngbae HWANG, Sol KIM, Saad KHALIL
  • Patent number: 12140926
    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: July 17, 2023
    Date of Patent: November 12, 2024
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, Eun-Sol Kim, Andrew Sundstrom
  • Publication number: 20240354975
    Abstract: A training data selection device for selecting training data and a training data selection method therefor are provided. The training data selection device includes a depth estimation network that applies depth estimation calculation to an input image obtained in real time to output depth distribution information corresponding to the input image. The device includes a vulnerability output device that outputs depth estimation vulnerability corresponding to the input image with reference to the depth distribution information. The device includes a training data acquisition support device that stores the input image and specific point cloud data corresponding to the input image as new training data in a certain storage space or transmits the input image and the specific point cloud data to another device, when it is determined that the depth estimation vulnerability is greater than or equal to a predetermined threshold.
    Type: Application
    Filed: November 28, 2023
    Publication date: October 24, 2024
    Applicants: HYUNDAI MOTOR COMPANY, KIA CORPORATION
    Inventors: Jin Sol Kim, Jin Ho Park, Jang Yoon Kim
  • Patent number: 12125236
    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: Grant
    Filed: March 9, 2021
    Date of Patent: October 22, 2024
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Matthew C. Putman, Vadim Pinskiy, Andrew Sundstrom, Aswin Raghav Nirmaleswaran, Eun-Sol Kim
  • Patent number: 12117799
    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: Grant
    Filed: November 6, 2020
    Date of Patent: October 15, 2024
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Andrew Sundstrom, Damas Limoge, Eun-Sol Kim, Vadim Pinskiy, Matthew C. Putman
  • Patent number: 12117812
    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: Grant
    Filed: June 18, 2021
    Date of Patent: October 15, 2024
    Assignee: Nanotronics Imaging, Inc.
    Inventors: Andrew Sundstrom, Eun-Sol Kim, Damas Limoge, Vadim Pinskiy, Matthew C. Putman