Patents by Inventor Abbas Sadat

Abbas Sadat 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).

  • Publication number: 20210276591
    Abstract: Systems and methods for generating semantic occupancy maps are provided. In particular, a computing system can obtain map data for a geographic area and sensor data obtained by the autonomous vehicle. The computer system can identify feature data included in the map data and sensor data. The computer system can, for a respective semantic object type from a plurality of semantic object types, determine, by the computing system and using feature data as input to a respective machine-learned model from a plurality of machine-learned models, one or more occupancy maps for one or more timesteps in the future, and wherein the respective machine-learned model is trained to determine occupancy for the respective semantic object type. The computer system can select a trajectory for the autonomous vehicle based on a plurality of occupancy maps associated with the plurality of semantic object types.
    Type: Application
    Filed: January 15, 2021
    Publication date: September 9, 2021
    Inventors: Raquel Urtasun, Abbas Sadat, Sergio Casas, Mengye Ren
  • Publication number: 20210200212
    Abstract: Systems and methods for generating motion plans for autonomous vehicles are provided. An autonomous vehicle can include a machine-learned motion planning system including one or more machine-learned models configured to generate target trajectories for the autonomous vehicle. The model(s) include a behavioral planning stage configured to receive situational data based at least in part on the one or more outputs of the set of sensors and to generate behavioral planning data based at least in part on the situational data and a unified cost function. The model(s) includes a trajectory planning stage configured to receive the behavioral planning data from the behavioral planning stage and to generate target trajectory data for the autonomous vehicle based at least in part on the behavioral planning data and the unified cost function.
    Type: Application
    Filed: March 20, 2020
    Publication date: July 1, 2021
    Inventors: Raquel Urtasun, Abbas Sadat, Mengye Ren, Andrei Pokrovsky, Yen-Chen Lin, Ersin Yumer
  • Publication number: 20210150244
    Abstract: Systems and methods for answering region specific questions are provided. A method includes obtaining a regional scene question including an attribute query and a spatial region of interest for a training scene depicting a surrounding environment of a vehicle. The method includes obtaining a universal embedding for the training scene and an attribute embedding for the attribute query of the scene question. The universal embedding can identify sensory data corresponding to the training scene that can be used to answer questions concerning a number of different attributes in the training scene. The attribute embedding can identify aspects of an attribute that can be used to answer questions specific to the attribute. The method includes determining an answer embedding based on the universal embedding and the attribute embedding and determining a regional scene answer to the regional scene question based on the spatial region of interest and the answer embedding.
    Type: Application
    Filed: September 8, 2020
    Publication date: May 20, 2021
    Inventors: Sean Segal, Wenjie Luo, Eric Randall Kee, Ersin Yumer, Raquel Urtasun, Abbas Sadat
  • Publication number: 20200159225
    Abstract: Systems and methods for generating motion plans including target trajectories for autonomous vehicles are provided. An autonomous vehicle may include or access a machine-learned motion planning model including a backbone network configured to generate a cost volume including data indicative of a cost associated with future locations of the autonomous vehicle. The cost volume can be generated from raw sensor data as part of motion planning for the autonomous vehicle. The backbone network can generate intermediate representations associated with object detections and objection predictions. The motion planning model can include a trajectory generator configured to evaluate one or more potential trajectories for the autonomous vehicle and to select a target trajectory based at least in part on the cost volume generate by the backbone network.
    Type: Application
    Filed: August 15, 2019
    Publication date: May 21, 2020
    Inventors: Wenyuan Zeng, Wenjie Luo, Abbas Sadat, Bin Yang, Raquel Urtasun
  • Publication number: 20200097008
    Abstract: An action planning system (100) and method for autonomous vehicles are provided. The system (100) comprises one or more processors (108) and one or more non-transitory computer-readable storage medium (110) having stored thereon a computer program used by the one or more processors (108), wherein the computer program causes the one or more processors (108) to estimate future environment of an autonomous vehicle (114), generate a possible trajectory for the autonomous vehicle (114), predict motion and reactions of each dynamic obstacle in the future environment of the autonomous vehicle (114) based on current local traffic context, and generate a prediction iteratively over timesteps.
    Type: Application
    Filed: March 7, 2018
    Publication date: March 26, 2020
    Inventors: Seyed Abbas Sadat, Thomas Glaser, Jason Scott Hardy, Mithun Jacob, Joerg Mueller