Delegation of object and pose detection

    公开(公告)号:US11170220B2

    公开(公告)日:2021-11-09

    申请号:US16742526

    申请日:2020-01-14

    申请人: X Development LLC

    摘要: Methods, apparatus, systems, and computer-readable media are provided for delegating object type and/or pose detection to a plurality of “targeted object recognition modules.” In some implementations, a method may be provided that includes: operating an object recognition client to facilitate object recognition for a robot; receiving, by the object recognition client, sensor data indicative of an observed object in an environment; providing, by the object recognition client, to each of a plurality of remotely-hosted targeted object recognition modules, data indicative of the observed object; receiving, by the object recognition client, from one or more of the plurality of targeted object recognition modules, one or more inferences about an object type or pose of the observed object; and determining, by the object recognition client, information about the observed object, such as its object type and/or pose, based on the one or more inferences.

    Automated data capture
    2.
    发明授权

    公开(公告)号:US11151744B1

    公开(公告)日:2021-10-19

    申请号:US16571841

    申请日:2019-09-16

    申请人: X Development LLC

    摘要: Methods for annotating objects within image frames are disclosed. Information is obtained that represents a camera pose relative to a scene. The camera pose includes a position and a location of the camera relative to the scene. Data is obtained that represents multiple images, including a first image and a plurality of other images, being captured from different angles by the camera relative to the scene. A 3D pose of the object of interest is identified with respect to the camera pose in at least the first image. A 3D bounding region for the object of interest in the first image is defined, which indicates a volume that includes the object of interest. A location and orientation of the object of interest is determined in the other images based on the defined 3D bounding region of the object of interest and the camera pose in the other images.

    MACHINE LEARNING METHODS AND APPARATUS FOR ROBOTIC MANIPULATION AND THAT UTILIZE MULTI-TASK DOMAIN ADAPTATION

    公开(公告)号:US20190084151A1

    公开(公告)日:2019-03-21

    申请号:US15913212

    申请日:2018-03-06

    申请人: X Development LLC

    IPC分类号: B25J9/16

    摘要: Implementations are directed to training a machine learning model that, once trained, is used in performance of robotic grasping and/or other manipulation task(s) by a robot. The model can be trained using simulated training examples that are based on simulated data that is based on simulated robot(s) attempting simulated manipulations of various simulated objects. At least portions of the model can also be trained based on real training examples that are based on data from real-world physical robots attempting manipulations of various objects. The simulated training examples can be utilized to train the model to predict an output that can be utilized in a particular task—and the real training examples used to adapt at least a portion of the model to the real-world domain can be tailored to a distinct task. In some implementations, domain-adversarial similarity losses are determined during training, and utilized to regularize at least portion(s) of the model.

    DELEGATION OF OBJECT AND POSE DETECTION

    公开(公告)号:US20180018518A1

    公开(公告)日:2018-01-18

    申请号:US15212967

    申请日:2016-07-18

    申请人: X DEVELOPMENT LLC

    IPC分类号: G06K9/00 G06K9/62

    摘要: Methods, apparatus, systems, and computer-readable media are provided for delegating object type and/or pose detection to a plurality of “targeted object recognition modules.” In some implementations, a method may be provided that includes: operating an object recognition client to facilitate object recognition for a robot; receiving, by the object recognition client, sensor data indicative of an observed object in an environment; providing, by the object recognition client, to each of a plurality of remotely-hosted targeted object recognition modules, data indicative of the observed object; receiving, by the object recognition client, from one or more of the plurality of targeted object recognition modules, one or more inferences about an object type or pose of the observed object; and determining, by the object recognition client, information about the observed object, such as its object type and/or pose, based on the one or more inferences.

    Selectively downloading targeted object recognition modules

    公开(公告)号:US10891484B2

    公开(公告)日:2021-01-12

    申请号:US16269183

    申请日:2019-02-06

    申请人: X DEVELOPMENT LLC

    摘要: Methods, apparatus, systems, and computer-readable media are provided for downloading targeted object recognition modules that are selected from a library of candidate targeted object recognition modules based on various signals. In some implementations, an object recognition client may be operated to facilitate object recognition for a robot. It may download targeted object recognition module(s). Each targeted object recognition module may facilitate inference of an object type or pose of an observed object. The targeted object module(s) may be selected from a library of targeted object recognition modules based on various signals, such as a task to be performed by the robot. The object recognition client may obtain vision data capturing at least a portion of an environment in which the robot operates. The object recognition client may determine, based on the vision data and the downloaded object recognition module(s), information about an observed object in the environment.

    GENERATING A MODEL FOR AN OBJECT ENCOUNTERED BY A ROBOT

    公开(公告)号:US20180349725A1

    公开(公告)日:2018-12-06

    申请号:US16042877

    申请日:2018-07-23

    申请人: X Development LLC

    摘要: Methods and apparatus related to generating a model for an object encountered by a robot in its environment, where the object is one that the robot is unable to recognize utilizing existing models associated with the robot. The model is generated based on vision sensor data that captures the object from multiple vantages and that is captured by a vision sensor associated with the robot, such as a vision sensor coupled to the robot. The model may be provided for use by the robot in detecting the object and/or for use in estimating the pose of the object.