Patents by Inventor Brian Andrew Ichter

Brian Andrew Ichter 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).

  • Systems and methods for training a machine learned model for agent navigation
    Patent number: 11436441
    Abstract: A computer-implemented method is disclosed for training one or more machine-learned models. The method can include inputting a first image frame and a second image frame into a feature disentanglement model and receiving, as an output of the machine-learned feature disentanglement model, a state feature and a perspective feature. The method can include inputting the state feature and the perspective feature into a machine-learned decoder model and receiving, as an output of the machine-learned decoder model, the reconstructed image frame. The method can include comparing the reconstructed image frame with a third image frame corresponding with the location and the perspective orientation. The method can include adjusting one or more parameters of the machine-learned feature disentanglement model based on the comparison of the reconstructed image frame and the third image frame.
    Type: Grant
    Filed: December 17, 2019
    Date of Patent: September 6, 2022
    Assignee: GOOGLE LLC
    Inventors: Jie Tan, Sehoon Ha, Tingnan Zhang, Xinlei Pan, Brian Andrew Ichter, Aleksandra Faust
  • Systems and Methods for Training a Machine Learned Model for Agent Navigation
    Publication number: 20210182620
    Abstract: A computer-implemented method is disclosed for training one or more machine-learned models. The method can include inputting a first image frame and a second image frame into a feature disentanglement model and receiving, as an output of the machine-learned feature disentanglement model, a state feature and a perspective feature. The method can include inputting the state feature and the perspective feature into a machine-learned decoder model and receiving, as an output of the machine-learned decoder model, the reconstructed image frame. The method can include comparing the reconstructed image frame with a third image frame corresponding with the location and the perspective orientation. The method can include adjusting one or more parameters of the machine-learned feature disentanglement model based on the comparison of the reconstructed image frame and the third image frame.
    Type: Application
    Filed: December 17, 2019
    Publication date: June 17, 2021
    Inventors: Jie Tan, Sehoon Ha, Tingnan Zhang, Xinlei Pan, Brian Andrew Ichter, Aleksandra Faust