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公开(公告)号：US12139164B2
公开(公告)日：2024-11-12
申请号：US17127882
申请日：2020-12-18
Applicant: Lyft, Inc.
Inventor： Lei Zhang , Li Jiang , Lukas Platinsky , Karim Tarek Mahmoud Elsayed Ahmed Shaban
Abstract: Examples disclosed herein involve a computing system configured to (i) obtain first sensor data captured by a first sensor of a vehicle during a given period of operation of the vehicle (ii) obtain second sensor data captured by a second sensor of the vehicle during the given period of operation of the vehicle, (iii) based on the first sensor data, localize the first sensor within a first coordinate frame of a first map layer, (iv) based on the second sensor data, localize the second sensor within a second coordinate frame of a second map layer, (v) based on a known transformation between the first coordinate frame and the second coordinate frame, determine respective poses for the first sensor and the second sensor in a common coordinate frame, and (vi) determine (a) a translation and (b) a rotation between the respective poses for the first and second sensors in the common coordinate frame.
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公开(公告)号：US11105905B2
公开(公告)日：2021-08-31
申请号：US16206966
申请日：2018-11-30
Applicant: Lyft, Inc.
Inventor： Forrest Samuel Briggs , Lei Zhang
Abstract: A method includes capturing, by a plurality of image sensors on an automotive vehicle, image data associated with one or more calibration objects in an environment, and capturing, by a LiDAR sensor, a three-dimensional LiDAR point cloud based on LiDAR data. The method further comprises generating a three-dimensional image point cloud based on the image data and the three-dimensional LiDAR point cloud, mapping a first alignment plane of the three-dimensional image point cloud relative to a second alignment plane of the three-dimensional LiDAR point cloud for each of the calibration objects to determine an angle between the first alignment plane and second alignment plane, and calibrating the LiDAR sensor relative to the image sensors by determining a degree of rotation of the LiDAR sensor to minimize the angle between the first alignment plane and second alignment plane.
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Patent Agency Ranking
公开(公告)号：US11875680B2
公开(公告)日：2024-01-16
申请号：US16983414
申请日：2020-08-03
Applicant: Lyft, Inc.
Inventor： Ashesh Jain , Yunjian Jiang , Mushfiqur Rouf , Henru Wang , Lei Zhang
CPC classification number: G08G1/165 , G05D1/0219 , G06V10/764 , G06V10/95 , G06V20/20 , G06V20/41 , G06V20/56 , G06V20/58
Abstract: Examples disclosed herein may involve a computing system that is configured to
(i) obtain previously-derived perception data for a collection of sensor data including a sequence of frames observed by a vehicle within one or more scenes, where the previously-derived perception data includes a respective set of object-level information for each of a plurality of objects detected within the sequence of frames, (ii) derive supplemental object-level information for at least one object detected within the sequence of frames that adds to the previously-derived object-level information for the at least one object, (iii) augment the previously-derived perception data to include the supplemental object-level information for the at least one object, and (iv) store the augmented perception data in an arrangement that encodes a hierarchical relationship between the plurality of objects, the sequence of frames, and the one or more scenes.-
公开(公告)号：US10733463B1
公开(公告)日：2020-08-04
申请号：US16836736
申请日：2020-03-31
Applicant: Lyft, Inc.
Inventor： Ashesh Jain , Yunjian Jiang , Mushfiqur Rouf , Henru Wang , Lei Zhang
Abstract: Examples disclosed herein may involve a computing system that is configured to (i) obtain previously-derived perception data for a collection of sensor data including a sequence of frames observed by a vehicle within one or more scenes, where the previously-derived perception data includes a respective set of object-level information for each of a plurality of objects detected within the sequence of frames, (ii) derive supplemental object-level information for at least one object detected within the sequence of frames that adds to the previously-derived object-level information for the at least one object, (iii) augment the previously-derived perception data to include the supplemental object-level information for the at least one object, and (iv) store the augmented perception data in an arrangement that encodes a hierarchical relationship between the plurality of objects, the sequence of frames, and the one or more scenes.
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公开(公告)号：US20210303877A1
公开(公告)日：2021-09-30
申请号：US16983414
申请日：2020-08-03
Applicant: Lyft, Inc.
Inventor： Ashesh Jain , Yunjian Jiang , Mushfiqur Rouf , Henru Wang , Lei Zhang
Abstract: Examples disclosed herein may involve a computing system that is configured to (i) obtain previously-derived perception data for a collection of sensor data including a sequence of frames observed by a vehicle within one or more scenes, where the previously-derived perception data includes a respective set of object-level information for each of a plurality of objects detected within the sequence of frames, (ii) derive supplemental object-level information for at least one object detected within the sequence of frames that adds to the previously-derived object-level information for the at least one object, (iii) augment the previously-derived perception data to include the supplemental object-level information for the at least one object, and (iv) store the augmented perception data in an arrangement that encodes a hierarchical relationship between the plurality of objects, the sequence of frames, and the one or more scenes.
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公开(公告)号：US20220194412A1
公开(公告)日：2022-06-23
申请号：US17127882
申请日：2020-12-18
Applicant: Lyft, Inc.
Inventor： Lei Zhang , Li Jiang , Lukas Platinsky , Karim Tarek Mahmoud Elsayed Ahmed Shaban
Abstract: Examples disclosed herein involve a computing system configured to (i) obtain first sensor data captured by a first sensor of a vehicle during a given period of operation of the vehicle (ii) obtain second sensor data captured by a second sensor of the vehicle during the given period of operation of the vehicle, (iii) based on the first sensor data, localize the first sensor within a first coordinate frame of a first map layer, (iv) based on the second sensor data, localize the second sensor within a second coordinate frame of a second map layer, (v) based on a known transformation between the first coordinate frame and the second coordinate frame, determine respective poses for the first sensor and the second sensor in a common coordinate frame, and (vi) determine (a) a translation and (b) a rotation between the respective poses for the first and second sensors in the common coordinate frame.
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公开(公告)号：US20200210887A1
公开(公告)日：2020-07-02
申请号：US16237321
申请日：2018-12-31
Applicant: Lyft, Inc.
Inventor： Ashesh Jain , Lei Zhang
Abstract: Systems, methods, and non-transitory computer-readable media can determine first sensor data captured by a first sensor of a vehicle. Second sensor data captured by a second sensor of the vehicle can be determined. Information describing the first sensor data and the second sensor data can be provided to a machine learning model trained to predict whether a pair of sensors are calibrated or mis-calibrated based on sensor data captured by the pair of sensors. A determination is made whether the first sensor and the second sensor are calibrated or mis-calibrated based on an output from the machine learning model.
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