Patents by Inventor Coline Manon Devin

Coline Manon Devin 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).

  • Self-supervised robotic object interaction
    Patent number: 10635944
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training an object representation neural network. One of the methods includes obtaining training sets of images, each training set comprising: (i) a before image of a before scene of the environment, (ii) an after image of an after scene of the environment after the robot has removed a particular object, and (iii) an object image of the particular object, and training the object representation neural network on the batch of training data, comprising determining an update to the object representation parameters that encourages the vector embedding of the particular object in each training set to be closer to a difference between (i) the vector embedding of the after scene in the training set and (ii) the vector embedding of the before scene in the training set.
    Type: Grant
    Filed: June 17, 2019
    Date of Patent: April 28, 2020
    Assignee: Google LLC
    Inventors: Eric Victor Jang, Sergey Vladimir Levine, Coline Manon Devin
  • SELF-SUPERVISED ROBOTIC OBJECT INTERACTION
    Publication number: 20190385022
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training an object representation neural network. One of the methods includes obtaining training sets of images, each training set comprising: (i) a before image of a before scene of the environment, (ii) an after image of an after scene of the environment after the robot has removed a particular object, and (iii) an object image of the particular object, and training the object representation neural network on the batch of training data, comprising determining an update to the object representation parameters that encourages the vector embedding of the particular object in each training set to be closer to a difference between (i) the vector embedding of the after scene in the training set and (ii) the vector embedding of the before scene in the training set.
    Type: Application
    Filed: June 17, 2019
    Publication date: December 19, 2019
    Inventors: Eric Victor Jang, Sergey Vladimir Levine, Coline Manon Devin