Patents by Inventor Xidi XUE

Xidi XUE 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).

  • Indoor monocular navigation method based on cross-sensor transfer learning and system thereof
    Patent number: 11561544
    Abstract: The present disclosure relates to an indoor monocular navigation method based on cross-sensor transfer learning and a system thereof. Determining an preliminary autonomous navigation model according to simulated laser radar data; acquiring actual single-line laser radar data and monocular camera data of the mobile robot simultaneously in an actual environment; determining the heading angle of the mobile robot according to the actual laser radar data; determining a laser radar monocular vision navigation model, according to the generated heading angle of the mobile robot and the monocular camera data at a the same moment and by using a Resnet18 network and a pre-trained YOLO v3 network; determining a heading angle of the mobile robot at the current moment, according to the acquired monocular camera data and by using the laser radar monocular vision navigation model; performing navigation of the mobile robot.
    Type: Grant
    Filed: July 17, 2020
    Date of Patent: January 24, 2023
    Assignee: HARBIN INSTITUTE OF TECHNOLOGY
    Inventors: Huijun Gao, Zhan Li, Xidi Xue, Weichao Sun, Xuebo Yang, Xinghu Yu
  • Indoor Monocular Navigation Method Based on Cross-Sensor Transfer Learning and System Thereof
    Publication number: 20210333793
    Abstract: The present invention relates to an indoor monocular navigation method based on cross-sensor transfer learning and a system thereof. Determining an preliminary autonomous navigation model according to simulated laser radar data; acquiring actual single-line laser radar data and monocular camera data of the mobile robot simultaneously in an actual environment; determining the heading angle of the mobile robot according to the actual laser radar data; determining a laser radar monocular vision navigation model, according to the generated heading angle of the mobile robot and the monocular camera data at a the same moment and by using a Resnet18 network and a pre-trained YOLO v3 network; determining a heading angle of the mobile robot at the current moment, according to the acquired monocular camera data and by using the laser radar monocular vision navigation model; performing navigation of the mobile robot.
    Type: Application
    Filed: July 17, 2020
    Publication date: October 28, 2021
    Inventors: Huijun GAO, Zhan LI, Xidi XUE, Weichao SUN, Xuebo YANG, Xinghu YU