公开(公告)号：US11315260B2

公开(公告)日：2022-04-26

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 ,  G05D1/00

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.

公开(公告)号：US20210326609A1

公开(公告)日：2021-10-21

申请号：US17224763

申请日：2021-04-07

Applicant: Waymo LLC

Inventor： Junhua Mao ,  Qian Yu ,  Congcong Li

IPC: G06K9/00 ,  G05D1/00 ,  G05D1/02 ,  G06K9/46 ,  G06K9/62 ,  G06N3/08

Abstract: Some aspects of the subject matter disclosed herein include a system implemented on one or more data processing apparatuses. The system can include an interface configured to obtain, from one or more sensor subsystems, sensor data describing an environment of a vehicle, and to generate, using the sensor data, (i) one or more first neural network inputs representing sensor measurements for a particular object in the environment and (ii) a second neural network input representing sensor measurements for at least a portion of the environment that encompasses the particular object and additional portions of the environment that are not represented by the one or more first neural network inputs; and a convolutional neural network configured to process the second neural network input to generate an output, the output including a plurality of feature vectors that each correspond to a different one a plurality of regions of the environment.

公开(公告)号：US11061406B2

公开(公告)日：2021-07-13

申请号：US16167007

申请日：2018-10-22

Applicant: Waymo LLC

Inventor： Junhua Mao ,  Congcong Li ,  Alper Ayvaci ,  Chen Sun ,  Kevin Murphy ,  Ruichi Yu

IPC: G05D1/02 ,  B60W30/095 ,  G01S17/93 ,  G05D1/00 ,  G06K9/00 ,  G06K9/62 ,  G01S17/931

Abstract: Aspects of the disclosure relate to training and using a model for identifying actions of objects. For instance, LIDAR sensor data frames including an object bounding box corresponding to an object as well as an action label for the bounding box may be received. Each sensor frame is associated with a timestamp and is sequenced with respect to other sensor frames. Each given sensor data frame may be projected into a camera image of the object based on the timestamp associated with the given sensor data frame in order to provide fused data. The model may be trained using the fused data such that the model is configured to, in response to receiving fused data, the model outputs an action label for each object bounding box of the fused data. This output may then be used to control a vehicle in an autonomous driving mode.

公开(公告)号：US10977501B2

公开(公告)日：2021-04-13

申请号：US16230187

申请日：2018-12-21

Applicant: Waymo LLC

Inventor： Junhua Mao ,  Qian Yu ,  Congcong Li

IPC: G06K9/00 ,  G05D1/00 ,  G05D1/02 ,  G06K9/46 ,  G06K9/62 ,  G06N3/08

Abstract: Some aspects of the subject matter disclosed herein include a system implemented on one or more data processing apparatuses. The system can include an interface configured to obtain, from one or more sensor subsystems, sensor data describing an environment of a vehicle, and to generate, using the sensor data, (i) one or more first neural network inputs representing sensor measurements for a particular object in the environment and (ii) a second neural network input representing sensor measurements for at least a portion of the environment that encompasses the particular object and additional portions of the environment that are not represented by the one or more first neural network inputs; and a convolutional neural network configured to process the second neural network input to generate an output, the output including a plurality of feature vectors that each correspond to a different one a plurality of regions of the environment.