SYSTEM AND METHOD FOR AUTOMATIC CONTAINER CONFIGURATION USING FIDUCIAL MARKERS

    公开(公告)号:US20220230339A1

    公开(公告)日:2022-07-21

    申请号:US17154472

    申请日:2021-01-21

    Abstract: Methods and systems for determining rotation and clipping parameters for images of unit load devices (ULDs) are disclosed herein. An example method includes capturing a set of image data featuring a ULD. The example method may further include locating a fiducial marker proximate to the ULD within the set of image data. The example method may further include cropping the set of image data, based upon the located fiducial marker, to generate a set of marker point data and a set of floor point data. The example method may further include rotating the set of image data based upon the set of marker point data and the set of floor point data, and clipping the rotated set of image data based upon the set of marker point data and the set of floor point data.

    METHODS FOR CALCULATING REAL TIME PACKAGE DENSITY

    公开(公告)号:US20210398308A1

    公开(公告)日:2021-12-23

    申请号:US16905606

    申请日:2020-06-18

    Inventor: Justin F. Barish

    Abstract: Methods and systems for assessing a unit load device (ULD) package density are disclosed herein. An example method includes capturing a primary and secondary image featuring the ULD. The method further includes segmenting the primary image and the secondary image into a plurality of subsections and determining a primary largest depth value and secondary largest depth value for each subsection. The method further includes determining a depth change by comparing the primary largest depth value for each subsection to the secondary largest depth value for each subsection. The method further includes clustering subsections in the secondary image including a respective secondary largest depth value that is substantially similar to a subsection corresponding to a depth change to create a plurality of clusters. The method further includes calculating a wasted volume, and calculating a ULD package density by subtracting the wasted volume from a filled volume of the ULD.

    THREE-DIMENSIONAL (3D) IMAGING SYSTEMS AND METHODS FOR DETECTING AND DIMENSIONING A VEHICLE STORAGE AREA

    公开(公告)号:US20210256682A1

    公开(公告)日:2021-08-19

    申请号:US16795243

    申请日:2020-02-19

    Abstract: Three-dimensional (3D) imaging systems and methods are disclosed for detecting and dimensioning a vehicle storage area. A 3D-depth camera captures 3D image data comprising one or more 3D image datasets of the vehicle storage area during corresponding one or more image capture iterations. A 3D data analytics application (app) executing on one or more processors communicatively coupled to the 3D-depth camera and for each one or more image capture iterations, updates a number of planar regions detected within the one or more 3D image datasets. The 3D data analytics app further assigns a vehicle storage area type to the vehicle storage area based on the number of planar regions detected by the 3D analytics app over the one or more image capture iterations.

    Methods for detecting if a time of flight (ToF) sensor is looking into a container

    公开(公告)号:US11009604B1

    公开(公告)日:2021-05-18

    申请号:US16779477

    申请日:2020-01-31

    Abstract: Methods for detecting if a Time of Flight (ToF) sensor is looking into a container are disclosed herein. An example method includes capturing a three-dimensional image. The three-dimensional image may comprise three-dimensional point data having a plurality of points. The example method may further include analyzing the plurality of points to determine a plurality of image components. Each image component may be representative of the plurality of points. The example method may further include comparing each image component of the plurality of image components to a threshold value. Each image component may correspond to a respective threshold value. The example method may further include determining that a number of image components N of the plurality of image components satisfy the respective threshold values, and determining the presence or absence of the container by comparing the number of image components N to an agreement threshold X.

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