-
公开(公告)号：US20210064890A1
公开(公告)日：2021-03-04
申请号：US16557246
申请日：2019-08-30
Applicant: Waymo LLC
Inventor： Hyman Murveit , Abhijit Ogale , Yu-Han Chen , Alper Ayvaci
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a future occupancy prediction for a region of an environment. In one aspect, a method comprises: receiving sensor data generated by a sensor system of a vehicle that characterizes an environment in a vicinity of the vehicle as of a current time point, wherein the sensor data comprises a plurality of sensor samples characterizing the environment that were each captured at different time points; processing a network input comprising the sensor data using a neural network to generate an occupancy prediction output for a region of the environment, wherein: the occupancy prediction output characterizes, for one or more future intervals of time after the current time point, a respective likelihood that the region of the environment will be occupied by an agent in the environment during the future interval of time.
-
公开(公告)号：US12204969B2
公开(公告)日：2025-01-21
申请号：US17893376
申请日：2022-08-23
Applicant: WAYMO LLC
Inventor： Justin Thorsen , Changchang Wu , Alper Ayvaci , Tiffany Chen , Lo Po Tsui , Zhinan Xu , Chen Wu , Sean Rafferty
IPC: G06K19/067 , G09F3/00
Abstract: Aspects of the disclosure provide for automatically generating labels for sensor data. For instance, first sensor data, for a vehicle may be identified. This first sensor data may have been captured by a first sensor of the vehicle at a first location during a first point in time and may be associated with a first label for an object. Second sensor data for the vehicle may be identified. The second sensor data may have been captured by a second sensor of the vehicle at a second location at a second point in time outside of the first point in time. The second location is different from the first location. A determination may be made as to whether the object is a static object. Based on the determination that the object is a static object, the first label may be used to automatically generate a second label for the second sensor data.
-
公开(公告)号：US11772654B2
公开(公告)日：2023-10-03
申请号：US17862499
申请日：2022-07-12
Applicant: Waymo LLC
Inventor： Hyman Murveit , Abhijit Ogale , Yu-Han Chen , Alper Ayvaci
IPC: B60W30/18 , G06T7/174 , G05D1/00 , G05D1/02 , G01S13/931 , G01S7/41 , G06V20/58 , G06F18/214 , G06V10/25 , G06V10/774 , G06V10/80
CPC classification number: B60W30/18159 , G01S7/417 , G01S13/931 , G05D1/0088 , G05D1/0212 , G05D1/0231 , G05D1/0257 , G06F18/2155 , G06T7/174 , G06V10/25 , G06V10/7753 , G06V10/811 , G06V20/58 , G01S2013/9323 , G05D2201/0213 , G06T2207/20084 , G06T2207/20132
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a future occupancy prediction for a region of an environment. In one aspect, a method comprises: receiving sensor data generated by a sensor system of a vehicle that characterizes an environment in a vicinity of the vehicle as of a current time point, wherein the sensor data comprises a plurality of sensor samples characterizing the environment that were each captured at different time points; processing a network input comprising the sensor data using a neural network to generate an occupancy prediction output for a region of the environment, wherein: the occupancy prediction output characterizes, for one or more future intervals of time after the current time point, a respective likelihood that the region of the environment will be occupied by an agent in the environment during the future interval of time.
-
公开(公告)号：US20220335624A1
公开(公告)日：2022-10-20
申请号：US17721288
申请日：2022-04-14
Applicant: Waymo LLC
Inventor： Daniel Rudolf Maurer , Austin Charles Stone , Alper Ayvaci , Anelia Angelova , Rico Jonschkowski
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network to predict optical flow. One of the methods includes obtaining a batch of one or more training image pairs; for each of the pairs: processing the first training image and the second training image using the neural network to generate a final optical flow estimate; generating a cropped final optical flow estimate from the final optical flow estimate; and training the neural network using the cropped optical flow estimate.
-
Patent Agency Ranking
公开(公告)号：US20220164585A1
公开(公告)日：2022-05-26
申请号：US17148148
申请日：2021-01-13
Applicant: Waymo LLC
Inventor： Alper Ayvaci , Feiyu Chen , Justin Yu Zheng , Bayram Safa Cicek , Vasiliy Igorevich Karasev
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network using contrastive learning. One of the methods includes obtaining a network input representing an environment; processing the network input using a first subnetwork of the neural network to generate a respective embedding for each location in the environment; processing the embeddings for each location in the environment using a second subnetwork of the neural network to generate a respective object prediction for each location; determining, for each of a plurality of pairs of the plurality of locations in the environment, whether the respective object predictions of the pair of locations characterize the same possible object or different possible objects; computing a respective contrastive loss value for each of the plurality of pairs of locations; and updating values for a plurality of parameters of the first subnetwork using the computed contrastive loss values.
-
公开(公告)号：US20210364637A1
公开(公告)日：2021-11-25
申请号：US17394861
申请日：2021-08-05
Applicant: Waymo LLC
Inventor： Yu-Han Chen , Wan-Yen Lo , Alper Ayvaci , Abhijit Ogale , Hyman Murveit
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a location of a particular object relative to a vehicle. In one aspect, a method includes obtaining sensor data captured by one or more sensors of a vehicle. The sensor data is processed by a convolutional neural network to generate a sensor feature representation of the sensor data. Data is obtained which defines a particular spatial region in the sensor data that has been classified as including sensor data that characterizes the particular object. An object feature representation of the particular object is generated from a portion of the sensor feature representation corresponding to the particular spatial region. The object feature representation of the particular object is processed using a localization neural network to generate the location of the particular object relative to the vehicle.
-
公开(公告)号：US20210303956A1
公开(公告)日：2021-09-30
申请号：US16827835
申请日：2020-03-24
Applicant: WAYMO LLC
Inventor： Justin Thorsen , Changchang Wu , Alper Ayvaci , Tiffany Chen , Lo Po Tsui , Zhinan Xu , Chen Wu , Sean Rafferty
IPC: G06K19/067 , G09F3/00
Abstract: Aspects of the disclosure provide for automatically generating labels for sensor data. For instance, first sensor data for a first vehicle may be identified. This first sensor data may have been captured by a first sensor of the vehicle at a first location during a first point in time and may be associated with a first label for an object. Second sensor data for a vehicle may be identified. The second sensor data may have been captured by a second sensor of the vehicle at a second location at a second point in time outside of the first point in time. The second location is different from the first location. The object is a static object may be determined. Based on the determination that the object is a static object, the first label may be used to automatically generate a second label for the second sensor data.
-
公开(公告)号：US11105924B2
公开(公告)日：2021-08-31
申请号：US16151880
申请日：2018-10-04
Applicant: Waymo LLC
Inventor： Yu-Han Chen , Wan-Yen Lo , Alper Ayvaci , Abhijit Ogale , Hyman Murveit
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a location of a particular object relative to a vehicle. In one aspect, a method includes obtaining sensor data captured by one or more sensors of a vehicle. The sensor data is processed by a convolutional neural network to generate a sensor feature representation of the sensor data. Data is obtained which defines a particular spatial region in the sensor data that has been classified as including sensor data that characterizes the particular object. An object feature representation of the particular object is generated from a portion of the sensor feature representation corresponding to the particular spatial region. The object feature representation of the particular object is processed using a localization neural network to generate the location of the particular object relative to the vehicle.
-
公开(公告)号：US11043003B2
公开(公告)日：2021-06-22
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
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.
-
-
-
-
-
-
-
-
Search Results
29
records
(took 0.023 seconds)
