Abstract: Methods and systems for optimizing one or more imaging settings for a machine vision job are disclosed herein. An example method includes detecting, by one or more processors, an initiation trigger that initiates the machine vision job. The example method further includes, responsive to detecting the initiation trigger, capturing, by an imaging device, a first image of a target object in accordance with a first configuration of the one or more imaging settings. The example method further includes, responsive to capturing the first image of the target object, automatically adjusting, by the one or more processors, the one or more imaging settings to a second configuration that includes at least one different imaging setting from the first configuration; and capturing, by the imaging device, a second image of the target object in accordance with the second configuration of the one or more imaging settings.

Abstract: Methods and systems for optimizing one or more imaging settings for a machine vision job are disclosed herein. An example method includes detecting, by one or more processors, an initiation trigger that initiates the machine vision job. The example method further includes, responsive to detecting the initiation trigger, capturing, by an imaging device, a first image of a target object in accordance with a first configuration of the one or more imaging settings. The example method further includes, responsive to capturing the first image of the target object, automatically adjusting, by the one or more processors, the one or more imaging settings to a second configuration that includes at least one different imaging setting from the first configuration; and capturing, by the imaging device, a second image of the target object in accordance with the second configuration of the one or more imaging settings.

Abstract: Methods and systems for optimizing performance of a machine vision system are disclosed herein. An example method includes obtaining one or more first and second images of a target object, where each of the one or more first and second images include a pass indication and a fail indication, respectively. The example method further includes conducting, by a feasibility setup tool, a feasibility setup analysis by (i) performing machine vision techniques on each of the one or more first and second images and (ii) generating a respective updated result indication for each of the one or more first and second images. The example method further includes comparing the respective updated result indication to the respective pass indications and fail indications for the one or more first and second images, respectively; and based on the comparing, generating one or more suggestions to optimize the performance of the machine vision system.

Abstract: An industrial Ethernet configuration tool with preview capabilities is disclosed herein. An example implementation includes a computing device for executing an application, the application operable to configure a machine vision job, wherein configuring the machine vision job includes: (1) configuring at least one tool to be executed by the imaging device during an execution of the job; (2) configuring an output data stream based on the at least one tool, the output data stream being formatted for communication to the a third-party computing device; and (3) displaying a representation of an output message, the output message being formed based on: (i) the configuring the output data stream, and (ii) previously acquired job run data, the output message being a representation of a transmission of a message from the imaging device to the third-party computing device.

Abstract: Methods and systems for optimizing a performance of a machine vision system are disclosed herein. An example method includes capturing, by an imaging device, an image of a target object in accordance with a set of imaging device settings. The example method further includes analyzing, by one or more processors, the image in accordance with a machine vision job. The example method further includes comparing, by the one or more processors, each of (i) the image to a baseline image, (ii) the machine vision job to a baseline machine vision job, and (iii) the set of imaging device settings to a baseline set of imaging device settings. The example method further includes, based on the comparing, generating, by the one or more processors, one or more suggestions to optimize the performance of the machine vision system.

Abstract: Methods and systems for optimizing one or more imaging settings for a machine vision job are disclosed herein. An example method includes detecting, by one or more processors, an initiation trigger that initiates the machine vision job. The example method further includes, responsive to detecting the initiation trigger, capturing, by an imaging device, a first image of a target object in accordance with a first configuration of the one or more imaging settings. The example method further includes, responsive to capturing the first image of the target object, automatically adjusting, by the one or more processors, the one or more imaging settings to a second configuration that includes at least one different imaging setting from the first configuration; and capturing, by the imaging device, a second image of the target object in accordance with the second configuration of the one or more imaging settings.

Abstract: Methods and systems for optimizing performance of a machine vision system are disclosed herein. An example method includes obtaining one or more first and second images of a target object, where each of the one or more first and second images include a pass indication and a fail indication, respectively. The example method further includes conducting, by a feasibility setup tool, a feasibility setup analysis by (i) performing machine vision techniques on each of the one or more first and second images and (ii) generating a respective updated result indication for each of the one or more first and second images. The example method further includes comparing the respective updated result indication to the respective pass indications and fail indications for the one or more first and second images, respectively; and based on the comparing, generating one or more suggestions to optimize the performance of the machine vision system.

Abstract: Methods and systems for tracking focus of an adjustable variable focus lens-based imaging system are disclosed. An example method includes identifying an initial focus position of an adjustable variable focus lens assembly and determining focusing parameters corresponding to that focus position. The focusing parameters are compared to a lens behavior model and a new, compensated focus position of the lens assembly is determined correcting for changes in lens assembly performance. A small window focusing sweep range, between forward and aft positions, may also be adjusted based on the lens behavior model to better identify the compensated focus position.

Abstract: Methods for creating a machine vision job including barcode scanning are disclosed. An example method may be performed by one or more processors and includes detecting a first configuration of a barcode scanning tool including settings of the barcode scanning tool, wherein the first configuration, when executed by a first imaging device operating in a fixed scanning mode, causes the first imaging device to execute the barcode scanning tool in accordance with the settings. The method also includes upgrading the first configuration to a second configuration of the barcode scanning tool, wherein the second configuration, when executed by a second imaging device operating in a machine vision mode, causes the second imaging device to execute the barcode scanning tool in accordance with the settings. The method further includes displaying a user-selectable option to add the barcode scanning tool configured in accordance with the second configuration to the machine vision job.

Abstract: Methods and systems for tracking focus of an adjustable variable focus lens-based imaging system are disclosed. An example method includes identifying an initial focus position of an adjustable variable focus lens assembly and determining focusing parameters corresponding to that focus position. The focusing parameters are compared to a lens behavior model and a new, compensated focus position of the lens assembly is determined correcting for changes in lens assembly performance. A small window focusing sweep range, between forward and aft positions, may also be adjusted based on the lens behavior model to better identify the compensated focus position.

Abstract: Systems and methods are provided for identifying an item in a inventory environment, by generating an augmented reality display of that environment, where that display includes an image identifier that points to a location of the item in that environment. The image identifier is generated by an augmented reality assembly, such as augmented reality glasses or a handheld barcode scanner with digital display. The augmented reality assembly may determine the location of the item, by detecting and tracking an electronic tag (passive or active) associated with the item. With the tag detected and tracked, the augmented reality assembly can generate the image identifier and place the image identifier in an augmented reality display of the inventory environment to identify to a user the location of that tag.

Abstract: The present invention relates generally to an adapter unit for a personal digital assistant. More specifically, this invention relates to an adapter unit that provides additional functionality, and improved ergonomics and increased ruggedness to the personal digital assistant. The additional functionality includes the ability to automatically change the function of one or more of the application buttons on the personal digital assistant upon the attachment of the adapter unit.

Abstract: The present invention relates generally to an adapter unit for a personal digital assistant. More specifically, this invention relates to an adapter unit that provides additional functionality, and improved ergonomics and increased ruggedness to the personal digital assistant. The additional functionality includes the ability to automatically change the function of one or more of the application buttons on the personal digital assistant upon the attachment of the adapter unit.

Abstract: The present invention relates generally to an adapter unit for a personal digital assistant. More specifically, this invention relates to an adapter unit that provides additional functionality, and improved ergonomics and increased ruggedness to the personal digital assistant. The additional functionality includes the ability to automatically change the function of one or more of the application buttons on the personal digital assistant upon the attachment of the adapter unit.

Abstract: The present invention relates generally to an adapter unit for a personal digital assistant. More specifically, this invention relates to an adapter unit that provides additional functionality, and improved ergonomics and increased ruggedness to the personal digital assistant. The additional functionality includes the ability to automatically change the function of one or more of the application buttons on the personal digital assistant upon the attachment of the adapter unit.

Abstract: The present invention relates generally to an adapter unit for a personal digital assistant. More specifically, this invention relates to an adapter unit that provides additional functionality, and improved ergonomics and increased ruggedness to the personal digital assistant. The additional functionality includes the ability to automatically change the function of one or more of the application buttons on the personal digital assistant upon the attachment of the adapter unit.