Patents by Inventor Jaspreet SAMBEE

Jaspreet SAMBEE 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).

  • Multi-level collaborative control system with dual neural network planning for autonomous vehicle control in a noisy environment
    Patent number: 11131992
    Abstract: A RLP system for a host vehicle includes a memory and levels. The memory stores a RLP algorithm, which is a multi-agent collaborative DQN with PER algorithm. A first level includes a data processing module that provides sensor data, object location data, and state information of the host vehicle and other vehicles. A second level includes a coordinate location module that, based on the sensor data, the object location data, the state information, and a refined policy provided by the third level, generates an updated policy and a set of future coordinate locations implemented via the first level. A third level includes evaluation and target neural networks and a processor that executes instructions of the RLP algorithm for collaborative action planning between the host and other vehicles based on outputs of the evaluation and target networks and to generate the refined policy based on reward values associated with events.
    Type: Grant
    Filed: November 30, 2018
    Date of Patent: September 28, 2021
    Assignees: DENSO International America, Inc.
    Inventors: Zhiyuan Du, Joseph Lull, Rajesh Malhan, Sriram Subramanian, Sushrut Bhalla, Jaspreet Sambee, Mark Crowley, Sebastian Fischmeister, Donghyun Shin, William Melek, Baris Fidan, Ami Woo, Bismaya Sahoo
  • Multi-Level Collaborative Control System With Dual Neural Network Planning For Autonomous Vehicle Control In A Noisy Environment
    Publication number: 20200174471
    Abstract: A RLP system for a host vehicle includes a memory and levels. The memory stores a RLP algorithm, which is a multi-agent collaborative DQN with PER algorithm. A first level includes a data processing module that provides sensor data, object location data, and state information of the host vehicle and other vehicles. A second level includes a coordinate location module that, based on the sensor data, the object location data, the state information, and a refined policy provided by the third level, generates an updated policy and a set of future coordinate locations implemented via the first level. A third level includes evaluation and target neural networks and a processor that executes instructions of the RLP algorithm for collaborative action planning between the host and other vehicles based on outputs of the evaluation and target networks and to generate the refined policy based on reward values associated with events.
    Type: Application
    Filed: November 30, 2018
    Publication date: June 4, 2020
    Inventors: Zhiyuan DU, Joseph LULL, Rajesh MALHAN, Sriram SUBRAMANIAN, Sushrut BHALLA, Jaspreet SAMBEE, Mark CROWLEY