Abstract: Disclosed are various embodiments for implementing passenger profiles for autonomous vehicles. A passenger of the autonomous vehicle is identified. A passenger profile corresponding to the passenger and comprising a passenger preference is identified. The passenger preference is identified. A configuration setting of the autonomous vehicle corresponding to autonomous operation of the autonomous vehicle is then adjusted based at least in part on the passenger preference.

Abstract: Systems and methods to improve video conferencing may include various improvements and modifications to image and audio data to simulate mutual presence among users. For example, automated positioning and presentation of image data of users via presentation devices may present users at a position, size, and scale to simulate mutual presence of users within a same physical space. In addition, rendering image data of users from virtual camera positions via presentation devices may simulate mutual eye gaze and mutual presence of users. Further, blending a background, or accentuating a user, within image data that is presented via presentation devices may match visual characteristics of the environment or the user to simulate mutual presence of users. Moreover, dynamic steering of individual audio transducers of an audio transducer array, and simulating audio point sources using a combination of speakers, may simulate direct communication and mutual presence of users.

Abstract: This disclosure describes a device and system for verifying the content of items in a bin within a materials handling facility. In some implementations, a bin content verification apparatus may pass by one or more bins and capture images of those bins. The images may be processed to determine whether the content included in the bins has changed since the last time images of the bins were captured. A determination may also be made as to whether a change to the bin content was expected and, if so, if the determined change corresponds with the expected change.

Abstract: A method for determining hard example sensor data inputs for training a task neural network is described. The task neural network is configured to receive a sensor data input and to generate a respective output for the sensor data input to perform a machine learning task. The method includes: receiving one or more sensor data inputs depicting a same scene of an environment, wherein the one or more sensor data inputs are taken during a predetermined time period; generating a plurality of predictions about a characteristic of an object of the scene; determining a level of inconsistency between the plurality of predictions; determining that the level of inconsistency exceeds a threshold level; and in response to the determining that the level of inconsistency exceeds a threshold level, determining that the one or more sensor data inputs comprise a hard example sensor data input.

Abstract: Systems and methods to improve video conferencing may include various improvements and modifications to image and audio data to simulate mutual presence among users. For example, automated positioning and presentation of image data of users via presentation devices may present users at a position, size, and scale to simulate mutual presence of users within a same physical space. In addition, rendering image data of users from virtual camera positions via presentation devices may simulate mutual eye gaze and mutual presence of users. Further, blending a background, or accentuating a user, within image data that is presented via presentation devices may match visual characteristics of the environment or the user to simulate mutual presence of users. Moreover, dynamic steering of individual audio transducers of an audio transducer array, and simulating audio point sources using a combination of speakers, may simulate direct communication and mutual presence of users.

Abstract: This disclosure describes a device and system for verifying the content of items in a bin within a materials handling facility. In some implementations, a bin content verification apparatus may pass by one or more bins and capture images of those bins. The images may be processed to determine whether the content included in the bins has changed since the last time images of the bins were captured. A determination may also be made as to whether a change to the bin content was expected and, if so, if the determined change corresponds with the expected change.

Abstract: Disclosed are various embodiments for implementing passenger profiles for autonomous vehicles. A passenger of the autonomous vehicle is identified. A passenger profile corresponding to the passenger and comprising a passenger preference is identified. The passenger preference is identified. A configuration setting of the autonomous vehicle corresponding to autonomous operation of the autonomous vehicle is then adjusted based at least in part on the passenger preference.

Abstract: This disclosure describes a device and system for verifying the content of items in a bin within a materials handling facility. In some implementations, a bin content verification apparatus may pass by one or more bins and capture images of those bins. The images may be processed to determine whether the content included in the bins has changed since the last time images of the bins were captured. A determination may also be made as to whether a change to the bin content was expected and, if so, if the determined change corresponds with the expected change.

Abstract: This disclosure describes a device and system for verifying the content of items in a bin within a materials handling facility. In some implementations, a bin content verification apparatus may pass by one or more bins and capture images of those bins. The images may be processed to determine whether the content included in the bins has changed since the last time images of the bins were captured. A determination may also be made as to whether a change to the bin content was expected and, if so, if the determined change corresponds with the expected change.

Abstract: Described are techniques for storing and retrieving items using a robotic device for moving items. Any combinations of image data depicting a manipulator interacting with an item, sensor data from sensors instrumenting the manipulator or item, item data regarding characteristics of the item, and constraint data relating to characteristics of the robotic device may be used to generate one or more configurations for the robotic device. The configurations may include points of contact and force vectors for contacting the item using the robotic device.

Abstract: Disclosed are various embodiments for obtaining environmental data and operational data from autonomous vehicles in a roadway. A vehicle state of the autonomous vehicles can be updated using data that is obtained from nearby vehicles or other vehicles that are on the roadway. The roadway management system can also generate updates to the vehicle state based upon data obtained from sources external to autonomous vehicles.

Abstract: Disclosed are various embodiments for implementing passenger profiles for autonomous vehicles. A passenger of the autonomous vehicle is identified. A passenger profile corresponding to the passenger and comprising a passenger preference is identified. The passenger preference is identified. A configuration setting of the autonomous vehicle corresponding to autonomous operation of the autonomous vehicle is then adjusted based at least in part on the passenger preference.

Abstract: Disclosed are various embodiments for implementing passenger profiles for autonomous vehicles. A passenger of the autonomous vehicle is identified. A passenger profile corresponding to the passenger and comprising a passenger preference is identified. The passenger preference is identified. A configuration setting of the autonomous vehicle corresponding to autonomous operation of the autonomous vehicle is then adjusted based at least in part on the passenger preference.

Abstract: Disclosed are various embodiments for non-mechanical assistance for autonomous vehicles. An unknown environmental condition may be detected that affects a navigation of the autonomous vehicle. A passenger and/or other source may be presented an inquiry requesting identification of the unknown environmental condition. A response to the inquiry may be used as an input by the vehicle control system in determining appropriate navigation of the autonomous vehicle.

Abstract: Imaging data regarding an interior portion of a storage vessel may be obtained from an imaging device (e.g., a digital camera or depth sensor) and interpreted in order to identify an available volume within the storage vessel. Where the imaging data includes an image of an interior of the storage vessel, an area of one or more contiguous spaces of a rear face of the storage vessel may be identified from the image and multiplied by a depth of the storage vessel in order to estimate the available volume. Where the imaging data includes a depth profile of the interior, the depth profile may be processed in order to estimate the available volume. Once an available volume has been estimated, the capacity of the available volume to accommodate one or more additional items may be determined, and information regarding the capacity may be provided to a user.

Abstract: This disclosure describes a device and system for verifying the content of items in a bin within a materials handling facility. In some implementations, a bin content verification apparatus may pass by one or more bins and capture images of those bins. The images may be processed to determine whether the content included in the bins has changed since the last time images of the bins were captured. A determination may also be made as to whether a change to the bin content was expected and, if so, if the determined change corresponds with the expected change.

Abstract: Described are techniques for storing and retrieving items using a robotic manipulator. Images depicting a human interacting with an item, sensor data from sensors instrumenting the human or item, data regarding physical characteristics of the item, and constraint data relating to the robotic manipulator or the item may be used to generate one or more configurations for the robotic manipulator. The configurations may include points of contact and force vectors for contacting the item using the robotic manipulator.

Abstract: Image classification and related imaging tasks performed using machine learning tools may be accelerated by using one or more of such tools to associate an image with a cluster of such labels or categories, and then to select one of the labels or categories of the cluster as associated with the image. The clusters of labels or categories may comprise labels that are mutually confused for one another, e.g., two or more labels or categories that have been identified as associated with a single image. By defining clusters of labels or categories, and configuring a machine learning tool to associate an image with one of the clusters, processes for identifying labels or categories associated with images may be accelerated because computations associated with labels or categories not included in the cluster may be omitted.

Abstract: Imaging data regarding an interior portion of a storage vessel may be obtained from an imaging device (e.g., a digital camera or depth sensor) and interpreted in order to identify an available volume within the storage vessel. Where the imaging data includes an image of an interior of the storage vessel, an area of one or more contiguous spaces of a rear face of the storage vessel may be identified from the image and multiplied by a depth of the storage vessel in order to estimate the available volume. Where the imaging data includes a depth profile of the interior, the depth profile may be processed in order to estimate the available volume. Once an available volume has been estimated, the capacity of the available volume to accommodate one or more additional items may be determined, and information regarding the capacity may be provided to a user.

Abstract: Radiographic imaging, or X-ray imaging, may be used to identify information regarding the contents of a container or other sealed object without having to open the container or the sealed object. One or more visual analyses of radiographic images may identify items within a container, or a condition of such items, as well as the portions or amounts of the contents of the container that correspond to air or dunnage. Additionally, a radiographic image may be projected onto an external surface of a container, or rendered within an augmented reality device or wearable computer device, thereby providing information regarding the contents of the container to a worker or other personnel within a vicinity of the container.