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31.发明申请公开(公告)号：US20190392596A1
公开(公告)日：2019-12-26
申请号：US16016495
申请日：2018-06-22
Applicant: X Development LLC
Inventor： Jie Yang , Cheng-en Guo , Elliott Grant
Abstract: Implementations relate to detecting/replacing transient obstructions from high-elevation digital images. A digital image of a geographic area includes pixels that align spatially with respective geographic units of the geographic area. Analysis of the digital image may uncover obscured pixel(s) that align spatially with geographic unit(s) of the geographic area that are obscured by transient obstruction(s). Domain fingerprint(s) of the obscured geographic unit(s) may be determined across pixels of a corpus of digital images that align spatially with the one or more obscured geographic units. Unobscured pixel(s) of the same/different digital image may be identified that align spatially with unobscured geographic unit(s) of the geographic area. The unobscured geographic unit(s) also may have domain fingerprint(s) that match the domain fingerprint(s) of the obscured geographic unit(s). Replacement pixel data may be calculated based on the unobscured pixels and used to generate a transient-obstruction-free version of the digital image.
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公开(公告)号：US20230045607A1
公开(公告)日：2023-02-09
申请号：US17964425
申请日：2022-10-12
Applicant: X Development LLC
Inventor： Jie Yang , Cheng-en Guo , Zhiqiang Yuan , Elliott Grant , Hongxu Ma
IPC: G06T7/00 , A01D41/127 , G06T5/50 , G06T7/143 , G06N3/04 , G06N3/08 , G06Q10/04 , G06Q50/02 , G06V20/13 , G06V20/10
Abstract: Implementations relate to detecting/replacing transient obstructions from high-elevation digital images, and/or to fusing data from high-elevation digital images having different spatial, temporal, and/or spectral resolutions. In various implementations, first and second temporal sequences of high-elevation digital images capturing a geographic area may be obtained. These temporal sequences may have different spatial, temporal, and/or spectral resolutions (or frequencies). A mapping may be generated of the pixels of the high-elevation digital images of the second temporal sequence to respective sub-pixels of the first temporal sequence. A point in time at which a synthetic high-elevation digital image of the geographic area may be selected. The synthetic high-elevation digital image may be generated for the point in time based on the mapping and other data described herein.
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公开(公告)号：US20220215037A1
公开(公告)日：2022-07-07
申请号：US17706317
申请日：2022-03-28
Applicant: X Development LLC
Inventor： David Clifford , Ming Zheng , Elliott Grant , Nanzhu Wang , Cheng-en Guo , Aleksandra Deis
IPC: G06F16/26 , G06F16/29 , G06F16/904 , G06F3/04847 , G06F16/9038 , G06F16/28 , G06Q50/02 , G06F16/248 , G06Q10/06 , G06F16/906
Abstract: Some implementations herein relate to a graphical user interface (GUI) that facilitates dynamically partitioning agricultural fields into clusters on an individual agricultural field-basis using agricultural features. A map of a geographic area containing a plurality of agricultural fields may be rendered as part of a GUI. The agricultural fields may be partitioned into a first set of clusters based on a first granularity value and agricultural features of individual agricultural fields. The individual agricultural fields may be visually annotated in the GUI to convey the first set of clusters of similar agricultural fields. Upon receipt of a second granularity value different from the first granularity value, the agricultural fields may be partitioned into a second set of clusters of similar agricultural fields. The map of the geographic area may be updated so that individual agricultural fields are visually annotated to convey the second set of clusters.
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公开(公告)号：US20210082133A1
公开(公告)日：2021-03-18
申请号：US17109433
申请日：2020-12-02
Applicant: X Development LLC
Inventor： Jie Yang , Cheng-en Guo , Elliott Grant
Abstract: Implementations relate to detecting/replacing transient obstructions from high-elevation digital images. A digital image of a geographic area includes pixels that align spatially with respective geographic units of the geographic area. Analysis of the digital image may uncover obscured pixel(s) that align spatially with geographic unit(s) of the geographic area that are obscured by transient obstruction(s). Domain fingerprint(s) of the obscured geographic unit(s) may be determined across pixels of a corpus of digital images that align spatially with the one or more obscured geographic units. Unobscured pixel(s) of the same/different digital image may be identified that align spatially with unobscured geographic unit(s) of the geographic area. The unobscured geographic unit(s) also may have domain fingerprint(s) that match the domain fingerprint(s) of the obscured geographic unit(s). Replacement pixel data may be calculated based on the unobscured pixels and used to generate a transient-obstruction-free version of the digital image.
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35.发明申请公开(公告)号：US20190191630A1
公开(公告)日：2019-06-27
申请号：US15854607
申请日：2017-12-26
Applicant: X Development LLC
Inventor： William Regan , Matthew Bitterman , David Brown , Elliott Grant , Zhiqiang Yuan
CPC classification number: A01G7/00 , A01G22/00 , B64C39/024 , B64C2201/127 , G05D1/0094 , G05D2201/0201 , G06K9/66 , G06T7/0004 , G06T11/60 , G06T2207/30188 , G09B5/06 , G09B19/003
Abstract: Systems and Methods for Augmented-Human Field Inspection Tools for Automated Phenotyping Systems and Agronomy Tools. In one embodiment, a method for plant phenotyping, includes: acquiring a first set of observations about plants in a field by a trainer. The trainer carries a sensor configured to collect observations about the plant, and the first set of observations includes ground truth data. The method also includes processing the first set of observations about the plants by a trait extraction model to generate instructions for a trainee; and acquiring a second set of observations about the plants by a trainee while the trainee follows the instructions.
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Patent Agency Ranking
公开(公告)号：US20230186529A1
公开(公告)日：2023-06-15
申请号：US17548169
申请日：2021-12-10
Applicant: X Development LLC
Inventor： Zhiqiang Yuan , Elliott Grant
CPC classification number: G06T11/001 , G06T7/60 , G06T7/90 , G06T2207/10024 , G06T2207/10116 , G06T2207/20081 , G06T2207/20084 , G06T2207/30188
Abstract: Implementations are described herein for colorizing an X-ray image and predicting one or more phenotypic traits about a plant based on the colorized X-ray image. In various implementations, an X-ray image that depicts a plant with a canopy of the plant partially occluding a part-of-interest is obtained, where the part-of-interest is visible through the canopy in the X-ray image. The X-ray images is colorized to predict one or more phenotypic traits of the part-of-interest. The colorization includes processing the X-ray image based on a machine learning model to generate a colorized version of the X-ray image, and predicting the one or more phenotypic traits based on one or more visual features of the colorized version of the X-ray image.
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公开(公告)号：US20230120944A1
公开(公告)日：2023-04-20
申请号：US17505058
申请日：2021-10-19
Applicant: X Development LLC
Inventor： Elliott Grant , Sergey Yaroshenko , Gabriella Levine
IPC: H04N13/239 , G06T7/80 , G06T7/73 , A01B79/00 , A01B76/00 , A01B63/02 , H04N13/296 , H04N13/246
Abstract: Implementations are disclosed for automatic commissioning, configuring, calibrating, and/or coordinating sensor-equipped modular edge computing devices that are mountable on agricultural vehicles. In various implementations, neighbor modular edge computing device(s) that are mounted on a vehicle nearest a given modular edge computing device may be detected based on sensor signal(s) generated by contactless sensor(s) of the given modular edge computing device. Based on the detected neighbor modular edge computing device(s), an ordinal position of the given modular edge computing device may be determined relative to a plurality of modular edge computing devices mounted on the agricultural vehicle. Based on the sensor signal(s), distance(s) to the neighbor modular edge computing device(s) may be determined. Extrinsic parameters of the given modular edge computing device may be determined based on the ordinal position of the given modular edge computing device and the distance(s).
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公开(公告)号：US11564357B2
公开(公告)日：2023-01-31
申请号：US17087219
申请日：2020-11-02
Applicant: X Development LLC
Inventor： William R. Regan , Matthew A. Bitterman , Benoit G. Schillings , David R. Brown , Elliott Grant
Abstract: In embodiments, acquiring sensor data associated with a plant growing in a field, and analyzing the sensor data to extract one or more phenotypic traits associated with the plant from the sensor data. Indexing the one or more phenotypic traits to one or both of an identifier of the plant or a virtual representation of a part of the plant, and determining one or more plant insights based on the one or more phenotypic traits, wherein the one or more plant insights includes information about one or more of a health, a yield, a planting, a growth, a harvest, a management, a performance, and a state of the plant. One or more of the health, yield, planting, growth, harvest, management, performance, and the state of the plant are included in a plant insights report that is generated.
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公开(公告)号：US20220391752A1
公开(公告)日：2022-12-08
申请号：US17342196
申请日：2021-06-08
Applicant: X Development LLC
Inventor： Elliott Grant , Kangkang Wang , Bodi Yuan , Zhiqiang Yuan
Abstract: Implementations are described herein for automatically generating labeled synthetic images that are usable as training data for training machine learning models to make an agricultural prediction based on digital images. A method includes: generating a plurality of simulated images, each simulated image depicting one or more simulated instances of a plant; for each of the plurality of simulated images, labeling the simulated image with at least one ground truth label that identifies an attribute of the one or more simulated instances of the plant depicted in the simulated image, the attribute describing both a visible portion and an occluded portion of the one or more simulated instances of the plant depicted in the simulated image; and training a machine learning model to make an agricultural prediction using the labeled plurality of simulated images.
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公开(公告)号：US20220219329A1
公开(公告)日：2022-07-14
申请号：US17683696
申请日：2022-03-01
Applicant: X Development LLC
Inventor： Zhiqiang Yuan , Elliott Grant
Abstract: Implementations are described herein for coordinating semi-autonomous robots to perform agricultural tasks on a plurality of plants with minimal human intervention. In various implementations, a plurality of robots may be deployed to perform a respective plurality of agricultural tasks. Each agricultural task may be associated with a respective plant of a plurality of plants, and each plant may have been previously designated as a target for one of the agricultural tasks. It may be determined that a given robot has reached an individual plant associated with the respective agricultural task that was assigned to the given robot. Based at least in part on that determination, a manual control interface may be provided at output component(s) of a computing device in network communication with the given robot. The manual control interface may be operable to manually control the given robot to perform the respective agricultural task.
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