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    GEO-MOTION AND APPEARANCE AWARE DATA ASSOCIATION
    31.
    发明申请
    GEO-MOTION AND APPEARANCE AWARE DATA ASSOCIATION 有权

    公开(公告)号：US20210192757A1

    公开(公告)日：2021-06-24

    申请号：US16726053

    申请日：2019-12-23

    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.

    AGENT TRAJECTORY PREDICTION USING TARGET LOCATIONS
    34.
    发明公开
    AGENT TRAJECTORY PREDICTION USING TARGET LOCATIONS 审中-公开

    公开(公告)号：US20240278803A1

    公开(公告)日：2024-08-22

    申请号：US18423136

    申请日：2024-01-25

    Applicant: Waymo LLC

    Inventor： Hang Zhao ,  Jiyang Gao ,  Chen Sun ,  Yi Shen ,  Yuning Chai ,  Cordelia Luise Schmid ,  Congcong Li ,  Benjamin Sapp ,  Dragomir Anguelov ,  Tian Lan ,  Yue Shen

    IPC: B60W60/00 ,  G06N3/02

    CPC classification number: B60W60/001 ,  G06N3/02 ,  B60W2420/403 ,  B60W2554/4049

    Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for predicting future trajectories for an agent in an environment. A system obtains scene context data characterizing the environment. The scene context data includes data that characterizes a trajectory of an agent in a vicinity of a vehicle in an environment up to a current time point. The system identifies a plurality of initial target locations in the environment. The system further generates, for each of a plurality of target locations that each corresponds to one of the initial target locations, a respective predicted likelihood score that represents a likelihood that the target location will be an intended final location for a future trajectory of the agent starting from the current time point. For each target location in a first subset of the target locations, the system generates a predicted future trajectory for the agent that is a prediction of the future trajectory of the agent given that the target location is the intended final location for the future trajectory. The system further selects, as likely future trajectories of the agent starting from the current time point, one or more of the predicted future trajectories.

    TRAINING A CLASSIFIER TO DETECT OPEN VEHICLE DOORS
    36.
    发明申请
    TRAINING A CLASSIFIER TO DETECT OPEN VEHICLE DOORS 有权

    公开(公告)号：US20230099920A1

    公开(公告)日：2023-03-30

    申请号：US17994991

    申请日：2022-11-28

    Applicant: Waymo LLC

    Inventor： Junhua Mao ,  Lo Po Tsui ,  Congcong Li ,  Edward Stephen Walker, JR.

    IPC: G06N3/08 ,  G06N3/04

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a classifier to detect open vehicle doors. One of the methods includes obtaining a plurality of initial training examples, each initial training example comprising (i) a sensor sample from a collection of sensor samples and (ii) data classifying the sensor sample as characterizing a vehicle that has an open door; generating a plurality of additional training examples, comprising, for each initial training example: identifying, from the collection of sensor samples, one or more additional sensor samples that were captured less than a threshold amount of time before the sensor sample in the initial training example was captured; and training the machine learning classifier on first training data that includes the initial training examples and the additional training examples to generate updated weights for the machine learning classifier.

    Neural networks for coarse- and fine-object classifications
    37.
    发明授权
    Neural networks for coarse- and fine-object classifications 有权

    公开(公告)号：US11361187B1

    公开(公告)日：2022-06-14

    申请号：US17118989

    申请日：2020-12-11

    Applicant: Waymo LLC

    Inventor： Junhua Mao ,  Congcong Li ,  Yang Song

    IPC: G06K9/62 ,  G05D1/02 ,  G06N3/04 ,  G06N3/08 ,  G06V20/56

    Abstract: Aspects of the subject matter disclosed herein include methods, systems, and other techniques for training, in a first phase, an object classifier neural network with a first set of training data, the first set of training data including a first plurality of training examples, each training example in the first set of training data being labeled with a coarse-object classification; and training, in a second phase after completion of the first phase, the object classifier neural network with a second set of training data, the second set of training data including a second plurality of training examples, each training example in the second set of training data being labeled with a fine-object classification.

    THREE-DIMENSIONAL LOCATION PREDICTION FROM IMAGES
    38.
    发明申请
    THREE-DIMENSIONAL LOCATION PREDICTION FROM IMAGES 有权

    公开(公告)号：US20220180549A1

    公开(公告)日：2022-06-09

    申请号：US17545987

    申请日：2021-12-08

    Applicant: Waymo LLC

    Inventor： Longlong Jing ,  Ruichi Yu ,  Jiyang Gao ,  Henrik Kretzschmar ,  Kang Li ,  Ruizhongtai Qi ,  Hang Zhao ,  Alper Ayvaci ,  Xu Chen ,  Dillon Cower ,  Congcong Li

    IPC: G06T7/70 ,  G06V10/40 ,  G06V10/80 ,  G06T7/50 ,  G06N20/00

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting three-dimensional object locations from images. One of the methods includes obtaining a sequence of images that comprises, at each of a plurality of time steps, a respective image that was captured by a camera at the time step; generating, for each image in the sequence, respective pseudo-lidar features of a respective pseudo-lidar representation of a region in the image that has been determined to depict a first object; generating, for a particular image at a particular time step in the sequence, image patch features of the region in the particular image that has been determined to depict the first object; and generating, from the respective pseudo-lidar features and the image patch features, a prediction that characterizes a location of the first object in a three-dimensional coordinate system at the particular time step in the sequence.

    SEARCHING AN AUTONOMOUS VEHICLE SENSOR DATA REPOSITORY BASED ON CONTEXT EMBEDDING
    39.
    发明申请
    SEARCHING AN AUTONOMOUS VEHICLE SENSOR DATA REPOSITORY BASED ON CONTEXT EMBEDDING 有权

    公开(公告)号：US20220164350A1

    公开(公告)日：2022-05-26

    申请号：US17104921

    申请日：2020-11-25

    Applicant: Waymo LLC

    Inventor： Jiyang Gao ,  Zijian Guo ,  Congcong Li ,  Xiaowei Li

    IPC: G06F16/2458 ,  G06F16/2455 ,  G06F16/248 ,  G06K9/00 ,  G06N3/08 ,  B60W60/00

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for searching an autonomous vehicle sensor data repository. One of the methods includes maintaining a collection of sensor samples and one or more embeddings of each sensor sample. Each sensor sample is generated from sensor data at multiple time steps and characterizes an environment at each of the multiple time steps. Each embedding corresponds to a respective portion of the sensor sample and has been generated by an embedding neural network. A query specifying a query portion of a query sensor sample is received. A query embedding corresponding to the query portion of the query sensor sample is generated through the embedding neural network. A plurality of relevant sensor samples that have embeddings that are closest to the query embedding are identified as characterizing similar scenarios to the query portion of the query sensor sample.

    RARE POSE DATA GENERATION
    40.
    发明申请
    RARE POSE DATA GENERATION 有权

    公开(公告)号：US20220156511A1

    公开(公告)日：2022-05-19

    申请号：US17528129

    申请日：2021-11-16

    Applicant: Waymo LLC

    Inventor： Xiaohan Jin ,  Junhua Mao ,  Ruizhongtai Qi ,  Congcong Li ,  Huayi Zeng

    IPC: G06K9/62 ,  G06K9/00 ,  G06T17/20 ,  G06T15/06 ,  G06T19/20 ,  G06N3/08

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating rare pose data. One of the methods includes obtaining a three-dimensional model of a dynamic object, wherein the dynamic object has multiple movable elements that define a plurality of poses of the dynamic object. A plurality of template poses of the dynamic object are used to generate additional poses for the dynamic object including varying angles of one or more key joints of the dynamic object according to the three-dimensional model. Point cloud data is generated for the additional poses generated for the dynamic object.

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