Abstract: Barcode readers with transflective mirrors are disclosed herein. An example barcode reader includes a housing and a window positioned within the housing, an imaging sensor and an illumination source positioned within the housing, and a transflective mirror positioned within the housing. The field-of-view of the imaging sensor is directed through the window along a first central axis of the field-of-view of the imaging sensor and the illumination pattern from the illumination source is directed through the window along a second central axis of the illumination pattern that is substantially parallel to the first central axis of the field-of-view of the imaging sensor.

Abstract: A method of auxiliary data capture control includes: storing, at a data capture device, (i) detection criteria corresponding to events having respective event identifiers; and (ii) a registration indicator associated with at least one of the event identifiers; controlling a primary data capture sensor to obtain primary captured data; in response to detecting, based on the primary captured data, that the detection criteria are satisfied for a detected one of the event identifiers, determining whether the registration indicator is associated with the detected event identifier; and when the registration indicator is associated with the detected event identifier, controlling an auxiliary data capture sensor to obtain auxiliary captured data.

Abstract: A navigational control method for a mobile automation apparatus includes: controlling a depth sensor to capture depth data representing a portion of a facility containing an obstacle; identifying the obstacle from the depth data; determining a probability that the obstacle is static; based on the probability, assigning the obstacle one of a dynamic class, a static class, and at least one intermediate class; updating a map to include a position of the obstacle, and the assigned class; and selecting, based on the assigned class, a navigational control action from a first action type associated with the dynamic class and the intermediate class, and a second action type associated with the static class.

Abstract: Methods and devices for improving indicia decoding with an imaging device are disclosed herein. An example method includes: (a) searching, by an imaging device, a search region within a current image for an indicia, wherein the search region includes a plurality of search seeds; (b) attempting, by the imaging device, to decode the indicia within the search region by analyzing image data corresponding to each seed of the plurality of search seeds; (c) responsive to not decoding the indicia, capturing, by the imaging device, a subsequent image featuring the indicia; (d) adjusting, by the imaging device, the search region based on a distance between the imaging device and the indicia featured in the subsequent image; (e) designating the subsequent image as the current image; and (f) iteratively performing (a)-(f) until the imaging device decodes the indicia.

Abstract: A mobile computing device including: a wireless communications interface configured to connect to a home access point; a controller configured to: control the wireless communications interface to initiate a scan for foreign access points and select a new access point from among the foreign access points; when the scan is complete, control the wireless communications interface to return to the home access point and initiate a home channel dwell time; control the wireless communications interface to receive data packets from the home access point during the home channel dwell time; and in response to a predefined criterion being met, control the wireless communications interface to connect to the new access point prior to expiry of the home channel dwell time.

Abstract: Methods and systems are provided for dimensioning a moving freight in motion along a path. An example system includes a plurality of laser line generators configured to emit coplanar laser beams forming a laser curtain oriented perpendicular to the floor and angled towards the direction of the path of the moving freight. A camera is configured to capture a series of two-dimensional images of the freight as it passes through the laser curtain. Additionally a positioning sensor is configured to detect the position and orientation of the moving freight as it passes through the laser curtain. A computing device in communication with the camera and the positioning sensor correlates each successive two-dimensional image with each corresponding position and orientation of the freight to obtain a composite three-dimensional shape of the freight. Furthermore, the computing device processes the composite three-dimensional shape of the freight to dimension the freight.

Abstract: An example disclosed printer configured to peel media from a backing, the printer having a peeler assembly that is engageable between a peeling position, wherein the printer is configured to peel the media from the backing, and a non-peeling position, wherein the printer is not configured to peel the media from the backing. The printer further including a sensor configured to send a signal corresponding to a position of the peeler assembly. The printer further including a communication interface configured to receive the position of the peeler assembly from the sensor and configured to transmit the position of the peeler assembly to a secondary component.

Abstract: A system includes: a mobile robot comprising a sensor, the robot further comprising a computer, the robot operating in an environment; a server operably connected to the robot via a communication system, the server configured to manage the robot; a controller operably connected to the robot, the controller operably connected to the server, the controller configured to control the robot; and an object of interest marked with a marker at one or more of an approximate height and an approximate field of view of the sensor, the sensor generating data describing the object of interest, the computer configured to identify one or more of the object of interest and the location using one or more of a shape of the object of interest and an intensity of data describing the object of interest.

Abstract: A computing device includes: a three-dimensional (3D) sensor configured to capture point cloud data from a field of view (FOV); an auxiliary sensor configured to capture reference depth measurements corresponding to a surface within the FOV; a controller connected with the 3D sensor and the auxiliary sensor, the controller configured to: detect a reference depth capture condition; when the reference depth capture condition satisfies a quality criterion, control the auxiliary sensor to capture a reference depth corresponding to the surface within the FOV; and initiate, based on the captured reference depth, generation of corrective data for use at the 3D sensor to capture the point cloud data.

Abstract: An example disclosed sheet includes a first layer; a second layer; a first die cut in the second layer defining a first wristband section and a second wristband section separated by a fold line; a second die cut in the first layer defining an imaging area; and a third die cut in the second layer defining an aperture in the second wristband section; wherein the aperture is surrounded by an adhesive and the aperture has an aperture dimension, the aperture dimension is greater than an inner dimension of the communication device, and the aperture dimension is less than an outer dimension of the communication device.

Abstract: A method comprising obtaining, from a sensor, depth data representing a target object; selecting a model to fit to the depth data; for each data point in the depth data: defining a ray from a location of the sensor to the data point; and determining an error based on a distance from the data point to the model along the ray; when the depth data does not meet a similarity threshold for the model based on the determined errors, selecting a new model and repeating the error determination for the depth data based on the new model; when the depth data meets the similarity threshold for the model, selecting the model as representing the target object; and outputting the selected model representing the target object.

Abstract: A method for detecting and dimensioning a target object includes: obtaining depth data representing a target object; defining a mask having a structure which decreases in density away from a central point of the mask; overlaying the mask on the depth data and selecting a subset of the depth data comprising data points which contact the mask; detecting a cluster of data points from the subset; detecting, based on the cluster, the target object; and outputting a representation of the target object.

Abstract: Device locationing using a beacon of a battery pack is described herein. A battery pack may determine that a user device is connected to the battery. The battery pack may determine, based on a power output of the battery, that the user device is inactive. The battery pack may cause, based on determining that the user device is inactive, the beacon to emit a beaconing signal that is associated with locating the user device and/or the battery pack.

Abstract: Systems and methods for automatic identification and presentation of edges, shapes and unique objects in an image used for machine vision job setup are disclosed herein. An example method includes receiving, by one or more processors, an image file. The method further includes automatically determining, by the one or more processors, an item of interest within the image file. The method further includes analyzing, by the one or more processors, the item of interest to determine an appropriate tool for processing the item of interest. The method further includes displaying, by the one or more processors, on a display screen: (i) an image corresponding to the image file, (ii) an indication of the item of interest, and (iii) an indication of the appropriate tool.

Abstract: A battery for a mobile device includes: a battery housing including an inner wall, an opposing outer wall, a rear wall, and an opposing forward wall, the rear and forward walls each joining the inner and outer walls; an electrical contact disposed on the inner wall, configured to engage with an electrical interface within a device housing; a seal on the inner wall surrounding the electrical contact and a further portion of the inner wall, and configured to engage a complementary surface within the device housing; a hook extending from the forward wall, configured to engage the device housing to establish a pivot axis of the battery housing during battery insertion and removal; and a latch extending from the rear wall, biased towards an extended position to secure the battery within the device housing, and movable to a retracted position to release the battery from the device housing.

Abstract: A method includes: obtaining a task definition including (i) an item identifier, (ii) an original item quantity, and (iii) a normalized item quantity; presenting the normalized item quantity; obtaining an image of a collected item set; deriving collected item data from the image; determining whether the collected item data matches the item identifier and the original item quantity; and generating first output data or second output data according to whether the collected item data matches the item identifier and the original item quantity, or does not match the item identifier and the original item quantity.

Abstract: In some implementations, a system may receive door position information that indicates a position of a door of a room. The system may receive, in association with a read operation of an RFID reader, first tag information associated with a first RFID tag, wherein the first tag information is received via a first antenna of the RFID reader, and wherein the RFID reader is disposed within the room and a first directional range of the first antenna is directed toward the door. The system may determine, based on the first tag information being received via the first antenna, a location status of the first RFID tag according to the door position information. The system may perform, based on the location status, an action associated with indicating a location of the first RFID tag.

Abstract: A kiosk includes a barcode reader module, vision camera, and central processing unit positioned within a housing. The housing defines a front surface and has an upper portion that extends outward past the front surface. The barcode reader module includes an imaging assembly with a first field-of-view that defines a product scanning region. The vision camera is positioned within the upper portion of the housing with at least a portion of the vision camera located forward of the front surface of the housing and has a second field-of-view facing generally downward and intersecting the first field-of-view of the barcode reader module within the product scanning region. The central processing unit is operatively connected to the barcode reader module and the vision camera and is configured to decode barcodes captured by the barcode reader module and perform advanced processing of images received from the vision camera.

Abstract: An example disclosed method includes, in response to receiving a first signal at a communication device when the communication device is in a deep sleep mode, changing the tag from the deep sleep mode to an awake mode for a period of time, wherein the communication device consumes a first amount of power in the deep sleep mode, and the communication device consumes a second amount of power in the awake mode, and the second amount of power is greater than the first amount of power; in response to receiving a second signal during the period of time when in the awake mode, changing the communication device from the awake mode to a fully functional mode, wherein the communication device consumes a third amount of power in the fully functional mode, and the third amount of power is greater than the second amount of power; and, in response to not receiving the second signal during the period of time, changing the communication device from the awake mode to the deep sleep mode.