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公开(公告)号：US11669980B2
公开(公告)日：2023-06-06
申请号：US17384654
申请日：2021-07-23
Applicant: Waymo LLC
Inventor： Daniel Rudolf Maurer , Alper Ayvaci , Nichola Abdo , Christopher John Sweeney , Robert William Anderson
CPC classification number: G06T7/269 , G06T7/248 , G06T2207/10028 , G06T2207/20084 , G06T2207/30261
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating motion detection based on optical flow. One of the methods includes obtaining a first image of a scene in an environment taken by an agent at a first time point and a second image of the scene at a second later time point. A point cloud characterizing the scene in the environment is obtained. A predicted optical flow is determined between the first image and the second image. A respective initial flow prediction for the point that represents motion of the point between the two time points is determined. A respective ego motion flow estimate for the point that represents a motion of the point induced by ego motion of the agent is determined. A respective motion prediction that indicates whether the point was static or in motion between the two time points is determined.
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公开(公告)号：US20230033989A1
公开(公告)日：2023-02-02
申请号：US17384654
申请日：2021-07-23
Applicant: Waymo LLC
Inventor： Daniel Rudolf Maurer , Alper Ayvaci , Nichola Abdo , Christopher John Sweeney , Robert William Anderson
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating motion detection based on optical flow. One of the methods includes obtaining a first image of a scene in an environment taken by an agent at a first time point and a second image of the scene at a second later time point. A point cloud characterizing the scene in the environment is obtained. A predicted optical flow is determined between the first image and the second image. A respective initial flow prediction for the point that represents motion of the point between the two time points is determined. A respective ego motion flow estimate for the point that represents a motion of the point induced by ego motion of the agent is determined. A respective motion prediction that indicates whether the point was static or in motion between the two time points is determined.
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公开(公告)号：US11782158B2
公开(公告)日：2023-10-10
申请号：US16229370
申请日：2018-12-21
Applicant: Waymo LLC
Inventor： David Lee , Xiaohan Jin , Congcong Li , Nichola Abdo
IPC: G01S17/58 , G01S17/06 , G01S17/89 , G06N3/08 , G06V10/82 , G06N7/01 , G06T7/20 , G06V20/58 , B60W30/095
CPC classification number: G01S17/58 , G01S17/06 , G01S17/89 , G06N3/08 , G06N7/01 , G06V10/82 , B60W30/0956 , G06T7/20 , G06T2207/10028 , G06T2207/30241 , G06T2207/30252 , G06V20/58
Abstract: Systems, methods, devices, and techniques for generating object-heading estimations. In one example, methods include actions of receiving sensor data representing measurements of an object that was detected within a proximity of a vehicle; processing the sensor data with one or more preliminary heading estimation subsystems to respectively generate one or more preliminary heading estimations for the object; processing two or more inputs with a second heading estimation subsystem to generate a refined heading estimation for the object, the two or more inputs including the one or more preliminary heading estimations for the object; and providing the refined heading estimation for the object to an external processing system.
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公开(公告)号：US12276752B2
公开(公告)日：2025-04-15
申请号：US17445129
申请日：2021-08-16
Applicant: Waymo LLC
Inventor： Xu Chen , Nichola Abdo , Ruichi Yu , Chang Gao
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.
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Patent Agency Ranking
公开(公告)号：US12106528B2
公开(公告)日：2024-10-01
申请号：US17684334
申请日：2022-03-01
Applicant: Waymo LLC
Inventor： Nichola Abdo , Jonathon Shlens , Zhifeng Chen , Christopher John Sweeney , Philipp Florian Jund
IPC: G06T9/00 , G06F18/214
CPC classification number: G06T9/002 , G06F18/2148
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting scene flow. One of the methods includes obtaining a current point cloud representing an observed scene at a current time point; obtaining object label data that identifies a first three-dimensional region in the observed scene; determining, for each current three-dimensional point that is within the first three-dimensional region and using the object label data, a respective preceding position of the current three-dimensional point at a preceding time point in a reference frame of the sensor at the current time point; and generating, using the preceding positions, a scene flow label for the current point cloud that comprises a respective ground truth motion vector for each of a plurality of the current three-dimensional points.
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公开(公告)号：US20220319054A1
公开(公告)日：2022-10-06
申请号：US17684334
申请日：2022-03-01
Applicant: Waymo LLC
Inventor： Nichola Abdo , Jonathon Shlens , Zhifeng Chen , Christopher John Sweeney , Philipp Florian Jund
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting scene flow. One of the methods includes obtaining a current point cloud representing an observed scene at a current time point; obtaining object label data that identifies a first three-dimensional region in the observed scene; determining, for each current three-dimensional point that is within the first three-dimensional region and using the object label data, a respective preceding position of the current three-dimensional point at a preceding time point in a reference frame of the sensor at the current time point; and generating, using the preceding positions, a scene flow label for the current point cloud that comprises a respective ground truth motion vector for each of a plurality of the current three-dimensional points.
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公开(公告)号：US11861481B2
公开(公告)日：2024-01-02
申请号：US16726060
申请日：2019-12-23
Applicant: Waymo LLC
Inventor： Zijian Guo , Nichola Abdo , Junhua Mao , Congcong Li , Edward Stephen Walker, Jr.
IPC: G06F16/53 , G06N3/042 , G06F16/538 , G06F16/535 , G05D1/00 , G05D1/02 , G06N3/08 , G06N3/045
CPC classification number: G06N3/042 , G05D1/0088 , G05D1/0221 , G06F16/535 , G06F16/538 , G06N3/045 , G06N3/08 , G05D2201/0213
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, for each sensor sample, an embedding of the sensor sample; receiving a request specifying a query sensor sample, wherein the query sensor sample characterizes a query environment region; and identifying, from the collection of sensor samples, a plurality of relevant sensor samples that characterize similar environment regions to the query environment region, comprising: processing the query sensor sample through the embedding neural network to generate a query embedding; and identifying, from sensor samples in a subset of the sensor samples in the collection, a plurality of sensor samples that have embeddings that are closest to the query embedding.
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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
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.
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公开(公告)号：US20230035454A1
公开(公告)日：2023-02-02
申请号：US17384637
申请日：2021-07-23
Applicant: Waymo LLC
Inventor： Daniel Rudolf Maurer , Alper Ayvaci , Robert William Anderson , Rico Jonschkowski , Austin Charles Stone , Anelia Angelova , Nichola Abdo , Christopher John Sweeney
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an optical flow label from a lidar point cloud. One of the methods includes obtaining data specifying a training example, including a first image of a scene in an environment captured at a first time point and a second image of the scene in the environment captured at a second time point. For each of a plurality of lidar points, a respective second corresponding pixel in the second image is obtained and a respective velocity estimate for the lidar point at the second time point is obtained. A respective first corresponding pixel in the first image is determined using the velocity estimate for the lidar point. A proxy optical flow ground truth for the training example is generated based on an estimate of optical flow of the pixel between the first and second images.
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