Patents by Inventor Gellert Sandor Mattyus

Gellert Sandor Mattyus 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).

  • Patent number: 11080537
    Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain a first type of sensor data (e.g., camera image data) associated with a surrounding environment of an autonomous vehicle and/or a second type of sensor data (e.g., LIDAR data) associated with the surrounding environment of the autonomous vehicle. The computing system can generate overhead image data indicative of at least a portion of the surrounding environment of the autonomous vehicle based at least in part on the first and/or second types of sensor data. The computing system can determine one or more lane boundaries within the surrounding environment of the autonomous vehicle based at least in part on the overhead image data indicative of at least the portion of the surrounding environment of the autonomous vehicle and a machine-learned lane boundary detection model.
    Type: Grant
    Filed: September 5, 2018
    Date of Patent: August 3, 2021
    Assignee: UATC, LLC
    Inventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrindihi Kowshika Lakshmikanth, Raquel Urtasun
  • Publication number: 20210146949
    Abstract: A computer-implemented method for localizing a vehicle can include accessing, by a computing system comprising one or more computing devices, a machine-learned retrieval model that has been trained using a ground truth dataset comprising a plurality of pre-localized sensor observations. Each of the plurality of pre-localized sensor observations has a predetermined pose value associated with a previously obtained sensor reading representation. The method also includes obtaining, by the computing system, a current sensor reading representation obtained by one or more sensors located at the vehicle. The method also includes inputting, by the computing system, the current sensor reading representation into the machine-learned retrieval model.
    Type: Application
    Filed: September 11, 2020
    Publication date: May 20, 2021
    Inventors: Julieta Martinez Covarrubias, Raquel Urtasun, Shenlong Wang, Ioan Andrei Barsan, Gellert Sandor Mattyus, Sasha Doubov, Hongbo Fan
  • Patent number: 10803325
    Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain rasterized LIDAR data associated with a surrounding environment of an autonomous vehicle. The rasterized LIDAR data can include LIDAR image data that is rasterized from a LIDAR point cloud. The computing system can access data indicative of a machine-learned lane boundary detection model. The computing system can input the rasterized LIDAR data associated with the surrounding environment of the autonomous vehicle into the machine-learned lane boundary detection model. The computing system can obtain an output from the machine-learned lane boundary detection model. The output can be indicative of one or more lane boundaries within the surrounding environment of the autonomous vehicle.
    Type: Grant
    Filed: September 5, 2018
    Date of Patent: October 13, 2020
    Assignee: UATC, LLC
    Inventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrindihi Kowshika Lakshmikanth, Raquel Urtasun, Wei-Chiu Ma
  • Publication number: 20190147254
    Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain a first type of sensor data (e.g., camera image data) associated with a surrounding environment of an autonomous vehicle and/or a second type of sensor data (e.g., LIDAR data) associated with the surrounding environment of the autonomous vehicle. The computing system can generate overhead image data indicative of at least a portion of the surrounding environment of the autonomous vehicle based at least in part on the first and/or second types of sensor data. The computing system can determine one or more lane boundaries within the surrounding environment of the autonomous vehicle based at least in part on the overhead image data indicative of at least the portion of the surrounding environment of the autonomous vehicle and a machine-learned lane boundary detection model.
    Type: Application
    Filed: September 5, 2018
    Publication date: May 16, 2019
    Inventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrindihi Kowshika Lakshmikanth, Raquel Urtasun
  • Publication number: 20190147320
    Abstract: A method includes obtaining training data including one or more images and one or more ground truth labels of the one or more images, and training an adversarial network including a siamese discriminator network and a generator network. The training includes generating, with the generator network, one or more generated images based on the one or more images; processing, with the siamese discriminator network, at least one pair of images to determine a prediction of whether the at least one pair of images includes the one or more generated images; and modifying, using a loss function of the adversarial network that depends on the ground truth label and the prediction, one or more parameters of the generator network.
    Type: Application
    Filed: November 15, 2018
    Publication date: May 16, 2019
    Inventors: Gellert Sandor Mattyus, Raquel Urtasun Sotil
  • Publication number: 20190147253
    Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain rasterized LIDAR data associated with a surrounding environment of an autonomous vehicle. The rasterized LIDAR data can include LIDAR image data that is rasterized from a LIDAR point cloud. The computing system can access data indicative of a machine-learned lane boundary detection model. The computing system can input the rasterized LIDAR data associated with the surrounding environment of the autonomous vehicle into the machine-learned lane boundary detection model. The computing system can obtain an output from the machine-learned lane boundary detection model. The output can be indicative of one or more lane boundaries within the surrounding environment of the autonomous vehicle.
    Type: Application
    Filed: September 5, 2018
    Publication date: May 16, 2019
    Inventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrindihi Kowshika Lakshmikanth, Raquel Urtasun, Wei-Chiu Ma