Patents by Inventor Yasasa Abeysirigoonawardena

Yasasa Abeysirigoonawardena 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).

  • Iterative generation of adversarial scenarios
    Patent number: 11036232
    Abstract: A method and apparatus for generating adversarial scenarios and training an autonomous driving agent for an autonomous vehicle, using one or more sets of parameters, each set of parameters defining a respective driving scenario. A new set of parameters is generated by changing one or more parameters of one of the sets of parameters to define a new driving scenario, and performance of the autonomous driving agent is evaluated on the new driving scenario. The generating and evaluating is repeated until the autonomous driving agent fails to satisfy a predefined performance threshold for the new driving scenario. Each instance of changing the one or more parameters is based on a prior evaluated performance of the autonomous driving agent. The autonomous driving agent is trained to update a learned policy of the autonomous driving agent using at least one set of parameters, including the new set of parameters.
    Type: Grant
    Filed: March 11, 2019
    Date of Patent: June 15, 2021
    Assignees: HUAWEI TECHNOLOGIES CO., LTD, THE ROYAL INSTITUTION FOR THE ADVANCEMENT OF LEARNING/MCGILL UNIVERSITY
    Inventors: Florian Shkurti, Gregory Dudek, Yasasa Abeysirigoonawardena, Elmira Amirloo Abolfathi, Jun Luo
  • ITERATIVE GENERATION OF ADVERSARIAL SCENARIOS
    Publication number: 20200089247
    Abstract: A method and apparatus for generating adversarial scenarios and training an autonomous driving agent for an autonomous vehicle, using one or more sets of parameters, each set of parameters defining a respective driving scenario. A new set of parameters is generated by changing one or more parameters of one of the sets of parameters to define a new driving scenario, and performance of the autonomous driving agent is evaluated on the new driving scenario. The generating and evaluating is repeated until the autonomous driving agent fails to satisfy a predefined performance threshold for the new driving scenario. Each instance of changing the one or more parameters is based on a prior evaluated performance of the autonomous driving agent. The autonomous driving agent is trained to update a learned policy of the autonomous driving agent using at least one set of parameters, including the new set of parameters.
    Type: Application
    Filed: March 11, 2019
    Publication date: March 19, 2020
    Inventors: Florian Shkurti, Gregory Dudek, Yasasa Abeysirigoonawardena, Elmira Amirloo Abolfathi, Jun Luo