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    Object Pickup Strategies for a Robotic Device
    5.
    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.

    Methods and systems for simultaneous localization and calibration
    6.
    发明授权
    Methods and systems for simultaneous localization and calibration 有权

    公开(公告)号：US11373395B2

    公开(公告)日：2022-06-28

    申请号：US16845544

    申请日：2020-04-10

    Applicant: X Development LLC

    Inventor： Dirk Holz ,  Troy Straszheim

    IPC: G06V10/70 ,  G06V10/75 ,  G01C21/20 ,  G05D1/02 ,  B66F9/00 ,  B66F9/075 ,  B66F9/06 ,  G06V20/10 ,  G06V20/56 ,  G06V30/196

    Abstract: Examples relate to simultaneous localization and calibration. An example implementation may involve receiving sensor data indicative of markers detected by a sensor on a vehicle located at vehicle poses within an environment, and determining a pose graph representing the vehicle poses and the markers. For instance, the pose graph may include edges associated with a cost function representing a distance measurement between matching marker detections at different vehicle poses. The distance measurement may incorporate the different vehicle poses and a sensor pose on the vehicle. The implementation may further involve determining a sensor pose transform representing the sensor pose on the vehicle that optimizes the cost function associated with the edges in the pose graph, and providing the sensor pose transform. In further examples, motion model parameters of the vehicle may be optimized as part of a graph-based system as well or instead of sensor calibration.

    Heterogeneous fleet of robots for collaborative object processing
    7.
    发明授权
    Heterogeneous fleet of robots for collaborative object processing 有权

    公开(公告)号：US09927815B2

    公开(公告)日：2018-03-27

    申请号：US15649080

    申请日：2017-07-13

    Applicant: X Development LLC

    Inventor： Stefan Nusser ,  Troy Straszheim ,  John Zevenbergen ,  Ethan Rublee

    IPC: G05D1/02 ,  B65G1/137 ,  B65G57/03

    CPC classification number: G05D1/0287 ,  B65G1/137 ,  B65G57/03 ,  G05B19/00 ,  G05D1/0297 ,  G05D2201/0216 ,  Y10S901/01

    Abstract: Example systems and methods may provide for a heterogeneous fleet of robotic devices for collaborative object processing in an environment, such as a warehouse. An example system includes a plurality of mobile robotic devices configured to transport one or more objects within an environment, a fixed robotic manipulator positioned within the environment that is configured to manipulate one or more objects within an area of reach of the fixed robotic manipulator, and a control system. The control system may be configured to cause one or more of the plurality of mobile robotic devices to deliver at least one object to at least one location within the area of reach of the fixed robotic manipulator, and to cause the fixed robotic manipulator to distribute the at least one object to a different one or more of the plurality of mobile robotic devices for delivery to one or more other locations within the environment.

    Heterogeneous fleet of robots for collaborative object processing
    8.
    发明授权
    Heterogeneous fleet of robots for collaborative object processing 有权

    公开(公告)号：US09733646B1

    公开(公告)日：2017-08-15

    申请号：US14537145

    申请日：2014-11-10

    Applicant: X Development LLC

    Inventor： Stefan Nusser ,  Troy Straszheim ,  John Zevenbergen ,  Ethan Rublee

    IPC: G05D1/02 ,  B65G1/137 ,  B65G57/03

    CPC classification number: G05D1/0287 ,  B65G1/137 ,  B65G57/03 ,  G05B19/00 ,  G05D1/0297 ,  G05D2201/0216 ,  Y10S901/01

    Abstract: Example systems and methods may provide for a heterogeneous fleet of robotic devices for collaborative object processing in an environment, such as a warehouse. An example system includes a plurality of mobile robotic devices configured to transport one or more objects within an environment, a fixed robotic manipulator positioned within the environment that is configured to manipulate one or more objects within an area of reach of the fixed robotic manipulator, and a control system. The control system may be configured to cause one or more of the plurality of mobile robotic devices to deliver at least one object to at least one location within the area of reach of the fixed robotic manipulator, and to cause the fixed robotic manipulator to distribute the at least one object to a different one or more of the plurality of mobile robotic devices for delivery to one or more other locations within the environment.

    Methods and Systems for Simultaneous Localization and Calibration
    9.
    发明申请
    Methods and Systems for Simultaneous Localization and Calibration 审中-公开

    公开(公告)号：US20200242396A1

    公开(公告)日：2020-07-30

    申请号：US16845544

    申请日：2020-04-10

    Applicant: X Development LLC

    Inventor： Dirk Holz ,  Troy Straszheim

    IPC: G06K9/62 ,  G01C21/20 ,  G05D1/02 ,  B66F9/00 ,  G06K9/00 ,  B66F9/075 ,  G06K9/68 ,  B66F9/06

    Abstract: Examples relate to simultaneous localization and calibration. An example implementation may involve receiving sensor data indicative of markers detected by a sensor on a vehicle located at vehicle poses within an environment, and determining a pose graph representing the vehicle poses and the markers. For instance, the pose graph may include edges associated with a cost function representing a distance measurement between matching marker detections at different vehicle poses. The distance measurement may incorporate the different vehicle poses and a sensor pose on the vehicle. The implementation may further involve determining a sensor pose transform representing the sensor pose on the vehicle that optimizes the cost function associated with the edges in the pose graph, and providing the sensor pose transform. In further examples, motion model parameters of the vehicle may be optimized as part of a graph-based system as well or instead of sensor calibration.

    Methods and systems for simultaneous localization and calibration
    10.
    发明授权
    Methods and systems for simultaneous localization and calibration 有权

    公开(公告)号：US10650270B2

    公开(公告)日：2020-05-12

    申请号：US15727726

    申请日：2017-10-09

    Applicant: X Development LLC

    Inventor： Dirk Holz ,  Troy Straszheim

    IPC: G06K9/62 ,  G01C21/20 ,  G05D1/02 ,  B66F9/00 ,  G06K9/00 ,  B66F9/075 ,  G06K9/68 ,  B66F9/06

    Abstract: Examples relate to simultaneous localization and calibration. An example implementation may involve receiving sensor data indicative of markers detected by a sensor on a vehicle located at vehicle poses within an environment, and determining a pose graph representing the vehicle poses and the markers. For instance, the pose graph may include edges associated with a cost function representing a distance measurement between matching marker detections at different vehicle poses. The distance measurement may incorporate the different vehicle poses and a sensor pose on the vehicle. The implementation may further involve determining a sensor pose transform representing the sensor pose on the vehicle that optimizes the cost function associated with the edges in the pose graph, and providing the sensor pose transform. In further examples, motion model parameters of the vehicle may be optimized as part of a graph-based system as well or instead of sensor calibration.

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