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    Methods and apparatus for determining the pose of an object based on point cloud data
    22.
    发明授权
    Methods and apparatus for determining the pose of an object based on point cloud data 有权

    公开(公告)号：US11192250B1

    公开(公告)日：2021-12-07

    申请号：US16665273

    申请日：2019-10-28

    Applicant: X Development LLC

    Inventor： Stefan Hinterstoisser

    IPC: B25J9/16 ,  G06F30/00

    Abstract: Methods, apparatus, and computer readable media that are related to 3D object detection and pose determination and that may optionally increase the robustness and/or efficiency of the 3D object recognition and pose determination. Some implementations are generally directed to techniques for generating an object model of an object based on model point cloud data of the object. Some implementations of the present disclosure are additionally and/or alternatively directed to techniques for application of acquired 3D scene point cloud data to a stored object model of an object to detect the object and/or determine the pose of the object.

    Machine learning methods and apparatus for robotic manipulation and that utilize multi-task domain adaptation
    23.
    发明授权
    Machine learning methods and apparatus for robotic manipulation and that utilize multi-task domain adaptation 有权

    公开(公告)号：US10773382B2

    公开(公告)日：2020-09-15

    申请号：US15913212

    申请日：2018-03-06

    Applicant: X Development LLC

    Inventor： Yunfei Bai ,  Kuan Fang ,  Stefan Hinterstoisser ,  Mrinal Kalakrishnan

    IPC: B25J9/16

    Abstract: 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.

    Automated data capture
    27.
    发明授权
    Automated data capture 有权

    公开(公告)号：US10417781B1

    公开(公告)日：2019-09-17

    申请号：US15396105

    申请日：2016-12-30

    Applicant: X Development LLC

    Inventor： Kurt Konolige ,  Nareshkumar Rajkumar ,  Stefan Hinterstoisser ,  Paul Wohlhart

    IPC: G06K9/46 ,  G06T7/73 ,  G06T7/60 ,  G06K9/62 ,  G06K9/66 ,  G06K9/52 ,  G06N3/08 ,  G06F16/583

    Abstract: 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.

    DELEGATION OF OBJECT AND POSE DETECTION
    28.
    发明申请
    DELEGATION OF OBJECT AND POSE DETECTION 审中-公开

    公开(公告)号：US20180300550A1

    公开(公告)日：2018-10-18

    申请号：US16014311

    申请日：2018-06-21

    Applicant: X Development LLC

    Inventor： Nareshkumar Rajkumar ,  Stefan Hinterstoisser

    IPC: G06K9/00 ,  G06K9/62 ,  G06T7/33

    CPC classification number: G06K9/00664 ,  G06K9/00979 ,  G06K9/6296 ,  G06T7/33 ,  G06T7/73 ,  G06T2207/10021

    Abstract: 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.

    Object Pickup Strategies for a Robotic Device
    29.
    发明申请
    Object Pickup Strategies for a Robotic Device 审中-公开

    公开(公告)号：US20180243904A1

    公开(公告)日：2018-08-30

    申请号：US15968323

    申请日：2018-05-01

    Applicant: X Development LLC

    Inventor： Gary Bradski ,  Steve Croft ,  Kurt Konolige ,  Ethan Rublee ,  Troy Straszheim ,  John Zevenbergen ,  Stefan Hinterstoisser ,  Hauke Strasdat

    IPC: B25J9/16 ,  H04N13/239 ,  G06T7/529 ,  G06T7/13 ,  B25J9/00 ,  G06K9/52 ,  G01B11/25 ,  G06K9/46

    Abstract: Example embodiments may relate to methods and systems for selecting a grasp point on an object. In particular, a robotic manipulator may identify characteristics of a physical object within a physical environment. Based on the identified characteristics, the robotic manipulator may determine potential grasp points on the physical object corresponding to points at which a gripper attached to the robotic manipulator is operable to grip the physical object. Subsequently, the robotic manipulator may determine a motion path for the gripper to follow in order to move the physical object to a drop-off location for the physical object and then select a grasp point, from the potential grasp points, based on the determined motion path. After selecting the grasp point, the robotic manipulator may grip the physical object at the selected grasp point with the gripper and move the physical object through the determined motion path to the drop-off location.

    Delegation of object and pose detection
    30.
    发明授权
    Delegation of object and pose detection 有权

    公开(公告)号：US10025984B2

    公开(公告)日：2018-07-17

    申请号：US15212967

    申请日：2016-07-18

    Applicant: X DEVELOPMENT LLC

    Inventor： Nareshkumar Rajkumar ,  Stefan Hinterstoisser

    IPC: G06K9/62 ,  G06K9/00 ,  G06T7/00

    Abstract: 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.

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