Symbol Technologies, LLC

Zebra Technologies Corporation

Arris Enterprises LLC

Arris Technology, Inc.

Andrew Wireless Systems Gmbh

Jay J Williams

Kevin J O'Connell

Yan Zhang

Cuneyt M Taskiran

Kevin J O'connell

Ankur R Patel

Bo Fu

Ye Gu

Thomas P Zwier

Lichen Wang

Bassam S Arshad

Michael Roger Garross

Neal A Fritz

Sean P Sweeney

Kevin Lynn Baum

Faisal Ishtiaq

Justin F Barish

Benedito J Fonseca, Jr

Adithya H Krishnamurthy

Loren J Rittle

Karthik Lakshminarayanan

Michael E Groble

Chih Huan Chien

Shivajit Mohapatra

Krunal S Shah

Sheida Gohari

David Korobov

Shivajit Mohaputra

Kevin L Baum

Jr Fonseca Benedito J

A method includes: obtaining, from a sensor disposed on a transporter, a set of beacon identifiers and proximity indicators, the beacon identifiers emitted by respective beacons mounted proximate to a boundary separating an exterior of a container from an interior of the container; determining whether the set of beacon identifiers and proximity indicators indicates a transition of the transporter across the boundary; when the determination is affirmative, detecting, based on the set of beacon identifiers and proximity indicators, a direction of travel of the transporter relative to the boundary; and generating a transition event including an identifier of the transporter, an identifier of the container, and the direction of travel.

Method, system and apparatus for detecting container transition events

A technique for real-time trailer utilization measurement includes a three-dimensional depth monitor operable to monitor loading of a trailer and a processor operable to determine trailer utilization in real-time during loading of the trailer using image information from the monitor. A graphical user interface can receive utilization information from the processor and display a visual representation of real-time loading of the trailer. Utilization is a ratio of cumulative package volume to currently loaded volume of the trailer, wherein the cumulative package volume is determined from dimensional scans of packages to be loaded in the trailer and the currently loaded volume is determined by the monitor.

Real-time trailer utilization measurement

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.

System and method for automatic container configuration using fiducial markers

A mount system for a monitoring device is disclosed. The mount system may include an extension arm attached to a device structure for housing the monitoring device. The mount system may include an alignment cup coupled to a support structure, wherein the extension arm is received through a through hole in a base of the alignment cup, and an oblong fitting attached to the extension arm opposite the device structure, wherein the oblong fitting is complementarily shaped to be received within the alignment cup to be received within the alignment cup, such that when the oblong fitting is received within the alignment cup, the device structure is aligned into a monitoring location. The mount system may include a dampening component between the support structure and the extension arm to bias the device structure into the monitoring location.

Mount system for a monitoring device

Three-dimensional (3D) depth imaging systems and methods are disclosed for assessing an orientation with respect to a container. A 3D-depth camera captures 3D image data of a shipping container. A container feature assessment application determines a representative container point cloud and (a) converts the 3D image data into 2D depth image data; (b) compares the 2D depth image data to one or more template image data; (c) performs segmentation to extract 3D point cloud features; (d) determines exterior features of the shipping container and assesses the exterior features using an exterior features metric; (e) determines interior features of the shipping container and assesses the interior features using an interior features metric; and (f) generates an orientation adjustment instruction for indicating to an operator to orient the 3D-depth camera in a second direction for use during a shipping container loading session, wherein the second direction is different than the first direction.

Systems and methods for automatic camera installation guide (CIG)

Systems and methods for automatic camera installation guidance (CIG)

A method of determining a location for placement of a package in an imaging controller includes: obtaining depth data of a package space; detecting an occluded portion of the depth data representing an area of the package space obstructed by an occlusion; retrieving stored unobstructed depth data representing the area of the package space in the absence of the occlusion; replacing the occluded portion with the unobstructed depth data to generate patched depth data; obtaining, based on the patched depth data, a location within the package space for placement of a package; and presenting an indication of the location.

System and method of determining a location for placement of a package

Methods, systems, and apparatus for segmenting and dimensioning objects are disclosed. An example method disclosed herein includes determining a first sensor of a plurality of sensors toward which a vehicle is moving based on image data generating by the plurality of sensors; designating the first sensor as a reference sensor; combining the image data from the plurality of sensors to generate combined image data representative of the vehicle and an object carried by the vehicle, the combining based on reference sensor; generating a plurality of clusters based on the combined image data; and identifying a first one of the clusters nearest the reference sensor as the object.

Methods, systems and apparatus for segmenting and dimensioning objects

A method and apparatus for receiving a depth frame from a depth sensor oriented towards an open end of a shipping container, the depth frame comprising a plurality of grid elements that each have a respective depth value, identifying one or more occlusions in the depth frame, correcting the one or more occlusions in the depth frame using one or more temporally proximate depth frames, and outputting the corrected depth frame for fullness estimation.

Methods and systems for occlusion detection and data correction for container-fullness estimation

Methods, systems and apparatus for segmenting objects are provided. A controller: receives, from one or more sensors, a 3D representation of a scene that includes an object represented by a 3D model; determines an orientation of a 2D image in the 3D representation by matching the 2D image with a corresponding region of the 3D representation; determines a first portion of the 3D representation that corresponds to a subset of the 3D model of the object from: the orientation of the 2D image in the 3D representation; and predetermined matching data representative of a matching of the 2D image with a respective corresponding region of the 3D model, each of the 3D model, the 2D image, and the predetermined matching data stored in a memory accessible to the controller; segments the first portion of the 3D representation from a second portion of the 3D representation.

Methods, systems and apparatus for segmenting objects

A method and apparatus for (a) receiving a three-dimensional (3D) point cloud from a depth sensor that is oriented towards an open end of a shipping container, the point cloud comprising a plurality of points that each have a respective depth value, (b) segmenting the received 3D point cloud among a plurality of grid elements, (c) calculating a respective loaded-container-portion grid-element volume for each grid element, (d) calculating a loaded-container-portion volume of the shipping container by aggregating the calculated respective loaded-container-portion grid-element volumes, (e) calculating an estimated fullness of the shipping container based on the loaded-container-portion volume and a capacity of the shipping container; and (f) outputting the calculated estimated fullness of the shipping container.

Methods and systems for automatic fullness estimation of containers

Image processing systems and methods are provided for extrinsic calibration of a plurality of image sensors. A logic circuit receives image data for an omnidirectional object from image sensors spaced apart and imaging at least a portion of a region of interest. The logic circuit combines the image data from the image sensors to generate a calibration matrix for the image sensors and to determine a matrix transformation data based on (i) reference image data and (ii) a three-dimensional model of the reference object. The logic circuit modifies the calibration matrix into an enhanced calibration matrix by applying the matrix transformation data to the calibration matrix, where the enhanced calibration matrix can be used to calibrate the plurality of image sensors.

Systems and methods for extrinsic calibration of a plurality of sensors

Dimensions of an object associated with an electro-optically readable code are estimated by aiming a handheld device at a scene containing the object supported on a base surface. A scanner on the device scans the scene over a field of view to obtain a position of a reference point of the code associated with the object, and reads the code. A dimensioning sensor on the device captures a three-dimensional (3D) point cloud of data points of the scene in automatic response to the reading of the code. A controller clusters the point cloud into data clusters, locates the reference point of the code in one of the data clusters, extracts from the point cloud the data points of the one data cluster belonging to the object, and processes the extracted data points belonging to the object to estimate the dimensions of the object.

Apparatus for and method of estimating dimensions of an object associated with a code in automatic response to reading the code

Growing community of inventors

Glenview, IL, United States of America

Jay J Williams