公开(公告)号：US20220156483A1

公开(公告)日：2022-05-19

申请号：US17527653

申请日：2021-11-16

Applicant: Waymo LLC

Inventor： Pei Sun ,  Weiyue Wang ,  Yuning Chai ,  Xiao Zhang ,  Dragomir Anguelov

IPC: G06K9/00 ,  G06T7/194

Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for performing object detection. The system obtains a respective range image corresponding to each point cloud in a set of point clouds captured by one or more sensors. The system processes each range image using a segmentation neural network to generate range image features and a segmentation output. The system generates a feature representation of the set of point clouds from only the feature representations of the foreground points. The system processes the feature representation of the set of point clouds using a prediction neural network to generate a prediction characterizing the set of point clouds.

公开(公告)号：US20220058858A1

公开(公告)日：2022-02-24

申请号：US17516073

申请日：2021-11-01

Applicant: Waymo LLC

Inventor： Yin Zhou ,  Pei Sun ,  Yu Zhang ,  Dragomir Anguelov ,  Jiyang Gao ,  Yu Ouyang ,  Zijian Guo ,  Jiquan Ngiam ,  Vijay Vasudevan

IPC: G06T15/20 ,  G06K9/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing point cloud data using dynamic voxelization. When deployed within an on-board system of a vehicle, processing the point cloud data using dynamic voxelization can be used to make autonomous driving decisions for the vehicle with enhanced accuracy, for example by combining representations of point cloud data characterizing a scene from multiple views of the scene.

公开(公告)号：US20210312177A1

公开(公告)日：2021-10-07

申请号：US16839693

申请日：2020-04-03

Applicant: Waymo LLC

Inventor： Mayank Bansal ,  Dragomir Anguelov

IPC: G06K9/00 ,  G06N3/04 ,  B60W60/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting occupancies of agents. One of the methods includes obtaining scene data characterizing a current scene in an environment; and processing a neural network input comprising the scene data using a neural network to generate a neural network output, wherein: the neural network output comprises respective occupancy outputs corresponding to a plurality of agent types at one or more future time points; the occupancy output for each agent type at a first future time point comprises respective occupancy probabilities for a plurality of locations in the environment; and in the occupancy output for each agent type at the first future time point, the respective occupancy probability for each location characterizes a likelihood that an agent of the agent type will occupy the location at the first future time point.

公开(公告)号：US20210150807A1

公开(公告)日：2021-05-20

申请号：US17099589

申请日：2020-11-16

Applicant: Waymo LLC

Inventor： Yin Zhou ,  Dragomir Anguelov ,  Zhangjie Cao

IPC: G06T17/00 ,  G06N3/04 ,  G06K9/00 ,  G06N20/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating realistic full-scene point clouds. One of the methods includes obtaining an initial scene point cloud characterizing an initial scene in an environment; obtaining, for each of one or more objects, an object point cloud that characterizes the object; and processing a first input comprising the initial scene point cloud and the one or more object point clouds using a first neural network that is configured to process the first input to generate a final scene point cloud that characterizes a transformed scene that has the one or more objects added to the initial scene.

公开(公告)号：US20210001897A1

公开(公告)日：2021-01-07

申请号：US16919872

申请日：2020-07-02

Applicant: Waymo LLC

Inventor： Yuning Chai ,  Benjamin Sapp ,  Mayank Bansal ,  Dragomir Anguelov

IPC: B60W60/00 ,  G06K9/62 ,  G06K9/00 ,  G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for agent trajectory prediction using anchor trajectories.

公开(公告)号：US12067738B2

公开(公告)日：2024-08-20

申请号：US17472418

申请日：2021-09-10

Applicant: Waymo LLC

Inventor： Alexander Gorban ,  Yin Zhou, Jr. ,  Dragomir Anguelov ,  Alessandro Giulianelli

IPC: G06T7/521 ,  G01S7/48 ,  G01S17/89 ,  G01S17/931 ,  G05D1/00 ,  G06T7/73

CPC classification number: G06T7/521 ,  G01S7/4808 ,  G01S17/89 ,  G01S17/931 ,  G05D1/0088 ,  G06T7/73 ,  G06T2207/10028 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining estimated ground truth object keypoint labels for sensor readings of objects. In one aspect, a method comprises obtaining a plurality of sets of label data for a sensor reading of an object; obtaining respective quality control data corresponding to each of the plurality of sets of label data, the respective quality control data comprising: data indicating whether the labeled location of the first object keypoint in the corresponding set of label data is accurate; and determining an estimated ground truth location for the first object keypoint in the sensor data keypoint from (i) the labeled locations that were indicated as accurate by the corresponding quality control data and (ii) not from the labeled locations that were indicated as not accurate by the corresponding quality control data.

公开(公告)号：US12051249B2

公开(公告)日：2024-07-30

申请号：US18216488

申请日：2023-06-29

Applicant: Waymo LLC

Inventor： Mayank Bansal ,  Dragomir Anguelov

IPC: G06V20/58 ,  B60W60/00 ,  G06N3/045 ,  G06N3/047 ,  G06V10/764 ,  G06V10/82 ,  G06V20/10

CPC classification number: G06V20/58 ,  B60W60/00259 ,  B60W60/00274 ,  G06N3/045 ,  G06N3/047 ,  G06V10/764 ,  G06V10/82 ,  G06V20/10

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting occupancies of agents. One of the methods includes obtaining scene data characterizing a current scene in an environment; and processing a neural network input comprising the scene data using a neural network to generate a neural network output, wherein: the neural network output comprises respective occupancy outputs corresponding to a plurality of agent types at one or more future time points; the occupancy output for each agent type at a first future time point comprises respective occupancy probabilities for a plurality of locations in the environment; and in the occupancy output for each agent type at the first future time point, the respective occupancy probability for each location characterizes a likelihood that an agent of the agent type will occupy the location at the first future time point.

公开(公告)号：US20240149906A1

公开(公告)日：2024-05-09

申请号：US17387852

申请日：2021-07-28

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 ,  B60W2420/42 ,  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.

公开(公告)号：US11941875B2

公开(公告)日：2024-03-26

申请号：US17443674

申请日：2021-07-27

Applicant: Waymo LLC

Inventor： Yuning Chai ,  Pei Sun ,  Jiquan Ngiam ,  Weiyue Wang ,  Vijay Vasudevan ,  Benjamin James Caine ,  Xiao Zhang ,  Dragomir Anguelov

IPC: G06V20/00 ,  G01S7/48 ,  G01S17/89 ,  G06F18/21 ,  G06F18/213 ,  G06F18/25 ,  G06N3/08 ,  G06T7/70 ,  G06V10/94 ,  H04N23/10

CPC classification number: G06V20/00 ,  G01S7/4802 ,  G01S17/89 ,  G06F18/213 ,  G06F18/217 ,  G06F18/253 ,  G06N3/08 ,  G06T3/4046 ,  G06T7/70 ,  G06V10/95 ,  H04N23/10 ,  G06T2207/20084

Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for processing a perspective view range image generated from sensor measurements of an environment. The perspective view range image includes a plurality of pixels arranged in a two-dimensional grid and including, for each pixel, (i) features of one or more sensor measurements at a location in the environment corresponding to the pixel and (ii) geometry information comprising range features characterizing a range of the location in the environment corresponding to the pixel relative to the one or more sensors. The system processes the perspective view range image using a first neural network to generate an output feature representation. The first neural network comprises a first perspective point-set aggregation layer comprising a geometry-dependent kernel.

公开(公告)号：US11922569B2

公开(公告)日：2024-03-05

申请号：US17713108

申请日：2022-04-04

Applicant: Waymo LLC

Inventor： Yin Zhou ,  Dragomir Anguelov ,  Zhangjie Cao

IPC: G06T17/00 ,  G06N3/045 ,  G06N20/00 ,  G06V20/10

CPC classification number: G06T17/00 ,  G06N3/045 ,  G06N20/00 ,  G06V20/10

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating realistic full-scene point clouds. One of the methods includes obtaining an initial scene point cloud characterizing an initial scene in an environment; obtaining, for each of one or more objects, an object point cloud that characterizes the object; and processing a first input comprising the initial scene point cloud and the one or more object point clouds using a first neural network that is configured to process the first input to generate a final scene point cloud that characterizes a transformed scene that has the one or more objects added to the initial scene.