Patents by Inventor Arthur Daniel Costea

Arthur Daniel Costea 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: 11623661
    Abstract: Techniques for controlling a vehicle based on height data and/or classification data being determined utilizing multi-channel image data are discussed herein. The vehicle can capture lidar data as it traverses an environment. The lidar data can be associated with a voxel space as three-dimensional data. Semantic information can be determined and associated with the lidar data and/or the three-dimensional voxel space. A multi-channel input image can be determined based on the three-dimensional voxel space and input into a machine learned (ML) model. The ML model can output data to determine height data and/or classification data associated with a ground surface of the environment. The height data and/or classification data can be utilized to determine a mesh associated with the ground surface. The mesh can be used to control the vehicle and/or determine additional objects proximate the vehicle.
    Type: Grant
    Filed: October 12, 2020
    Date of Patent: April 11, 2023
    Assignee: Zoox, Inc.
    Inventors: Arthur Daniel Costea, Robert Evan Mahieu, David Pfeiffer, Zeng Wang
  • Publication number: 20230095410
    Abstract: Techniques for detecting and classifying objects using lidar data are discussed herein. In some cases, the system may be configured to utilize a predetermined number of prior frames of lidar data to assist with detecting and classifying objects. In some implementations, the system may utilize a subset of the data associated with the prior lidar frames together with the full set of data associated with a current frame to detect and classify the objects.
    Type: Application
    Filed: September 24, 2021
    Publication date: March 30, 2023
    Inventors: Arthur Daniel Costea, David Pfeiffer, Zeng Wang, Allan Zelener
  • Publication number: 20220111868
    Abstract: Techniques for estimating ground height based on lidar data are discussed herein. A vehicle captures lidar data as it traverses an environment. The lidar data can be associated with a voxel space as three-dimensional data. Semantic information can be determined and associated with the lidar data and/or the three-dimensional voxel space. A multi-channel input image can be determined based on the three-dimensional voxel space and input into a machine learned (ML) model. The ML model can output data to determine height data and/or classification data associated with a ground surface of the environment. The height data and/or classification data can be utilized to determine a mesh associated with the ground surface. The mesh can be used to control the vehicle and/or determine additional objects proximate the vehicle.
    Type: Application
    Filed: October 12, 2020
    Publication date: April 14, 2022
    Inventors: Arthur Daniel Costea, Robert Evan Mahieu, David Pfeiffer, Zeng Wang