Hand Held Products, Inc.

Manjul Bizoara

Jingzhe Zhang

Wei Zhao

David M Wilz

Taylor Smith

David Wilz, Sr

Shankar Ban

John F Waldron

Marinedrive Piskaladhanabalan

Sri Teja Gadamsetti

Douglas Hinson

Venkata Sudhakar Bulusu

Embodiments of the disclosure include methods, computer program products, and apparatuses configured for selecting a lens focusing scheme based on a detectability level of an aimer pattern. An imaging engine projects an aimer pattern onto a target object within a field of view of a first imager of an imaging engine. The imaging engine acquires a first image of the target object via the first imager. The imaging engine selects a lens focusing scheme based on a detectability level of the aimer pattern in the first image, in which selection of the lens focusing scheme is between a first lens focusing scheme associated with a location of the aimer pattern and a second lens focusing scheme associated with at least one predefined lens position. The imaging engine determines a focus position for a lens in accordance with the lens focusing scheme.

Apparatuses, methods, and computer program products for comprehensive focusing in imaging environments

Various embodiments disclose a method for tracking assets. Method includes determining one or more locations of an asset within an indoor environment based on metadata associated an RF signal received from an RF tag associated with the asset. The method further includes identifying a first set of locations of the one or more locations. The method further includes identifying a second set of locations of the one or more locations, wherein the second set of locations corresponds to uncalibrated locations of the asset within indoor environment. Additionally, the method includes receiving a third set of locations of the asset. Furthermore, the method includes training a machine learning (ML) model based on the first set of locations, the second set of locations, and the third set of locations, and the metadata associated with the RF signal. The ML model predicts a fourth set of locations of another asset.

Methods and systems of estimating location of an asset within material handling environment

Embodiments described include apparatuses, computer program products, and methods for automatic proof of delivery, for example by capturing and decoding a visual indicia. Some embodiments minimize possibilities of errors, false proof, and/or the like in item delivery. At least one embodiment enables automatic proof of delivery in a multi-sensor environment. Example embodiments are configured for capturing an image data object set utilizing at least one of an image sensor set, where the image data object set includes a captured-indicia image data object including a visual indicia; decoding the visual indicia to identify delivery information; identifying a delivery proof image data object from the image data object set; and processing the delivery proof image data object for use as a proof of delivery. Some embodiments include a near-field image sensor for capturing the delivery proof image data object and a far-field sensor for capturing the captured-indicia image data object.

Apparatuses, methods, and computer program products for automatic proof of delivery using visual indicia

Embodiments of the present disclosure provide for automatic item searching and verification. In example contexts, embodiments provide such functionality to improve the accuracy and efficiency of item searching during item loading and/or unloading, such as when delivering packages. Some embodiments provide for capturing an image, or set of images, identifying relevant items represented in the captured images, generating augmented reality elements associated with such relevant items, and rendering the augmented reality elements in an augmented reality environment, which can be maintained as the user continues to perform user action. Some embodiments additionally or alternatively detect improper actions based on captured image(s), and generate and provide notifications to a user for viewing.

Apparatuses, computer-implemented methods, and computer program products for automatic item searching and verification

A method for alerting a user on an electronic device is described. The method includes identifying a signal at an ultrasound transmission frequency received at a first electronic device from a second electronic device. Further, the method includes receiving timing information corresponding to an exchange of an ultrasound transmission between the first electronic device and the second electronic device. Furthermore, a first distance value between the first electronic device and the second electronic device is computed by performing a time of flight estimation using the timing information. Furthermore, the first distance value is refined by using an output of a machine learning model to determine a second distance value. Furthermore, the method includes generating an alert based on the comparison of the second distance value with a predefined threshold distance value. In some examples, the alert can be indicative of a violation of a physical distancing norm in an environment.

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Charlotte, NC, United States of America

Manjul Bizoara