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    END-TO-END OBJECT TRACKING USING NEURAL NETWORKS WITH ATTENTION
    11.
    发明申请
    END-TO-END OBJECT TRACKING USING NEURAL NETWORKS WITH ATTENTION 有权

    公开(公告)号：US20250078927A1

    公开(公告)日：2025-03-06

    申请号：US18953053

    申请日：2024-11-19

    Applicant: Waymo LLC

    Inventor： Ruichi Yu ,  Xu Chen ,  Shiwei Sheng ,  Luming Tang ,  Chieh-En Tsai

    IPC: G11C16/04 ,  G11C7/20 ,  G11C8/08 ,  G11C16/14 ,  G11C16/34

    Abstract: The described aspects and implementations enable efficient calibration of a sensing system of a vehicle. In one implementation, disclosed is a method and a system to perform the method, the system including the sensing system configured to obtain a plurality of images associated with a corresponding time of a plurality of times. The system further includes a data processing system operatively coupled to the sensing system and configured to generate a plurality of sets of feature tensors (FTs) associated with one or more objects of the environment depicted in a respective image. The data processing system is further to obtain a combined FT and process the combined FT using a neural network to identify one or more tracks characterizing motion of a respective object.

    OBJECT TRACKING ACROSS A WIDE RANGE OF DISTANCES FOR DRIVING APPLICATIONS
    12.
    发明申请
    OBJECT TRACKING ACROSS A WIDE RANGE OF DISTANCES FOR DRIVING APPLICATIONS 有权

    公开(公告)号：US20250022143A1

    公开(公告)日：2025-01-16

    申请号：US18221577

    申请日：2023-07-13

    Applicant: Waymo LLC

    Inventor： Qinru Li ,  Longlong Jing ,  Ruichi Yu ,  Xu Chen ,  Shiwei Sheng

    IPC: G06T7/20 ,  G01S17/89 ,  G05D1/02 ,  G06V10/25 ,  G06V10/44 ,  G06V20/56

    Abstract: The described aspects and implementations enable efficient and seamless tracking of objects in vehicle environments using different sensing modalities across a wide range of distances. A perception system of a vehicle deploys an object tracking pipeline with a plurality of models that include a camera model trained to perform, using camera images, object tracking at distances exceeding a lidar sensing range, a lidar model trained to perform, using lidar images, object tracking at distances within the lidar sensing range, and a camera-lidar model trained to transfer, using the camera images and the lidar images, object tracking from the camera model to the lidar model.

    LONG-RANGE OBJECT DETECTION, LOCALIZATION, TRACKING AND CLASSIFICATION FOR AUTONOMOUS VEHICLES
    13.
    发明申请
    LONG-RANGE OBJECT DETECTION, LOCALIZATION, TRACKING AND CLASSIFICATION FOR AUTONOMOUS VEHICLES 有权

    公开(公告)号：US20250014357A1

    公开(公告)日：2025-01-09

    申请号：US18892711

    申请日：2024-09-23

    Applicant: Waymo LLC

    Inventor： Ruichi Yu ,  Kang Li ,  Tao Han ,  Robert Cosgriff ,  Henrik Kretzschmar

    IPC: G06V20/58 ,  G01S13/931 ,  G01S17/931 ,  G06F18/22

    Abstract: Aspects of the disclosure relate to controlling a vehicle. For instance, using a camera, a first camera image including a first object may be captured. A first bounding box for the first object and a distance to the first object may be identified. A second camera image including a second object may be captured. A second bounding box for the second image and a distance to the second object may be identified. Whether the first object is the second object may be determined using a plurality of models to compare visual similarity of the two bounding boxes, to compare a three-dimensional location based on the distance to the first object and a three-dimensional location based on the distance to the second object, and to compare results from the first and second models. The vehicle may be controlled in an autonomous driving mode based on a result of the third model.

    IDENTIFICATION OF SPURIOUS RADAR DETECTIONS IN AUTONOMOUS VEHICLE APPLICATIONS
    15.
    发明申请
    IDENTIFICATION OF SPURIOUS RADAR DETECTIONS IN AUTONOMOUS VEHICLE APPLICATIONS 有权

    公开(公告)号：US20230046274A1

    公开(公告)日：2023-02-16

    申请号：US17445129

    申请日：2021-08-16

    Applicant: Waymo LLC

    Inventor： Xu Chen ,  Nichola Abdo ,  Ruichi Yu ,  Chang Gao

    IPC: G01S7/41 ,  G06K9/00 ,  G06K9/62 ,  G06T7/20 ,  G01S13/86 ,  G01S13/931 ,  B60W60/00

    Abstract: The described aspects and implementations enable fast and accurate verification of radar detection of objects in autonomous vehicle (AV) applications using combined processing of radar data and camera images. In one implementation, disclosed is a method and a system to perform the method that includes obtaining a radar data characterizing intensity of radar reflections from an environment of the AV, identifying, based on the radar data, a candidate object, obtaining a camera image depicting a region where the candidate object is located, and processing the radar data and the camera image using one or more machine-learning models to obtain a classification measure representing a likelihood that the candidate object is a real object.

    GEO-MOTION AND APPEARANCE AWARE DATA ASSOCIATION
    16.
    发明申请
    GEO-MOTION AND APPEARANCE AWARE DATA ASSOCIATION 有权

    公开(公告)号：US20220245835A1

    公开(公告)日：2022-08-04

    申请号：US17728682

    申请日：2022-04-25

    Applicant: Waymo LLC

    Inventor： Ruichi Yu ,  Sachithra Madhawa Hemachandra ,  Ian James Mahon ,  Congcong Li

    IPC: G06T7/246 ,  G06N3/04 ,  G06N3/08

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for associating a new measurement of an object surrounding a vehicle with a maintained track. One of the methods includes receiving an object track for a particular object, receiving a new measurement characterizing a new object at a new time step, and determining whether the new object is the same as the particular object, comprising: generating a representation of the new object at the new and preceding time steps; generating a representation of the particular object at the new and preceding time steps; processing a first network input comprising the representations using a first neural network to generate an embedding of the first network input; and processing the embedding of the first network input using a second neural network to generate a predicted likelihood that the new object and the particular object are the same.

    Interacted Object Detection Neural Network
    17.
    发明申请
    Interacted Object Detection Neural Network 有权

    公开(公告)号：US20210295555A1

    公开(公告)日：2021-09-23

    申请号：US17342434

    申请日：2021-06-08

    Applicant: Waymo LLC

    Inventor： Alper Ayvaci ,  Yu-Han Chen ,  Ruichi Yu ,  Chen Wu ,  Noha Waheed Ahmed Radwan ,  Jonathon Shlens

    IPC: G06T7/73 ,  G06T7/50 ,  G06K9/62 ,  G06N3/08 ,  G06N3/04

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating object interaction predictions using a neural network. One of the methods includes obtaining a sensor input derived from data generated by one or more sensors that characterizes a scene. The sensor input is provided to an object interaction neural network. The object interaction neural network is configured to process the sensor input to generate a plurality of object interaction outputs. Each respective object interaction output includes main object information and interacting object information. The respective object interaction outputs corresponding to the plurality of regions in the sensor input are received as output of the object interaction neural network.

    Interacted Object Detection Neural Network
    18.
    发明申请
    Interacted Object Detection Neural Network 有权

    公开(公告)号：US20210150752A1

    公开(公告)日：2021-05-20

    申请号：US16686840

    申请日：2019-11-18

    Applicant: Waymo LLC

    Inventor： Alper Ayvaci ,  Yu-Han Chen ,  Ruichi Yu ,  Chen Wu ,  Noha Waheed Ahmed Radwan ,  Jonathon Shlens

    IPC: G06T7/73 ,  G06T7/50 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating object interaction predictions using a neural network. One of the methods includes obtaining a sensor input derived from data generated by one or more sensors that characterizes a scene. The sensor input is provided to an object interaction neural network. The object interaction neural network is configured to process the sensor input to generate a plurality of object interaction outputs. Each respective object interaction output includes main object information and interacting object information. The respective object interaction outputs corresponding to the plurality of regions in the sensor input are received as output of the object interaction neural network.

    End-to-end object tracking using neural networks with attention
    19.
    发明授权
    End-to-end object tracking using neural networks with attention 有权

    公开(公告)号：US12175767B2

    公开(公告)日：2024-12-24

    申请号：US17715838

    申请日：2022-04-07

    Applicant: Waymo LLC

    Inventor： Ruichi Yu ,  Xu Chen ,  Shiwei Sheng ,  Luming Tang ,  Chieh-En Tsai

    IPC: G06V20/58 ,  B60W60/00 ,  G06T7/20 ,  G06V10/62 ,  G06V10/82

    Abstract: The described aspects and implementations enable efficient calibration of a sensing system of a vehicle. In one implementation, disclosed is a method and a system to perform the method, the system including the sensing system configured to obtain a plurality of images associated with a corresponding time of a plurality of times. The system further includes a data processing system operatively coupled to the sensing system and configured to generate a plurality of sets of feature tensors (FTs) associated with one or more objects of the environment depicted in a respective image. The data processing system is further to obtain a combined FT and process the combined FT using a neural network to identify one or more tracks characterizing motion of a respective object.

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