Abstract: A support structure for manufacturing a pressure vessel, the support structure configured to be carried on a supporting substrate, the support structure comprising a first segment support structure nestable within, and moveable relative to, a second segment support structure, wherein the first segment support structure is configured to be raised and lowered relative to the second segment support structure to thereby raise and lower the first segment relative to the substrate, and the first segment support structure is configured to move between a nested position within the second segment support structure to a position spaced apart from the second segment support structure across a surface of the substrate.

Abstract: Aspects of the disclosure provide for depot behaviors for autonomous vehicles. For instance, a signal to control an autonomous vehicle to a depot area may be received from a server computing device. A prioritized list of staging areas within the depot area may be identified. Each staging area of the prioritized list of staging areas enables the vehicle to observe stopping locations at which a need of the vehicle may be addressed. The vehicle may be controlled to a first staging area of the prioritized list. Once the vehicle has reached the first staging area, whether a stopping location that meets one or more needs of the vehicle is available may be determined. When is available, the vehicle may be controlled to the available stopping location. When not available, the vehicle may be controlled to a second staging area of the prioritized list.

Abstract: A communication, safety, and location system for use as part of a goods transporting system comprises a plurality of tile units 2, the tile units 2 configured to tesselate to form a substantially continuous grid with a substantially flat upper surface and to enable movement of cargo carrying units positioned on the surface in use; a number of the tile units at locations spaced within the grid equipped with UWB transceivers.

Abstract: Some embodiments provide retail product ordering systems comprising: a user computing device comprising an application executed by a device control circuit to: receive an audible utterance; controls a product identifier application interface to: apply a tokenizer model and obtain a set of individual search words; apply a series of featurizer models to the search words to generate features; and apply a classifier and extractor model based on the features and generate multiple requested product entities each comprising a respective sub-set of the position labeled product terms; wherein the device control circuit is further configured to access a purchase history database, confirm an accuracy of each of requested product entities relative to a purchase history, generate a listing of determined product identifiers corresponding to the confirmed set of the multiple requested product entities, and control a display system of the user computing device to render the listing of determined product identifiers.

Abstract: A support structure for manufacturing a pressure vessel, the support structure configured to be carried on a supporting substrate, the support structure comprising a first segment support structure nestable within, and moveable relative to, a second segment support structure, wherein the first segment support structure is configured to be raised and lowered relative to the second segment support structure to thereby raise and lower the first segment relative to the substrate, and the first segment support structure is configured to move between a nested position within the second segment support structure to a position spaced apart from the second segment support structure across a surface of the substrate.

Abstract: Some embodiments provide retail product ordering systems comprising: a user computing device comprising an application executed by a device control circuit to: receive an audible utterance; controls a product identifier application interface to: apply a tokenizer model and obtain a set of individual search words; apply a series of featurizer models to the search words to generate features; and apply a classifier and extractor model based on the features and generate multiple requested product entities each comprising a respective sub-set of the position labeled product terms; wherein the device control circuit is further configured to access a purchase history database, confirm an accuracy of each of requested product entities relative to a purchase history, generate a listing of determined product identifiers corresponding to the confirmed set of the multiple requested product entities, and control a display system of the user computing device to render the listing of determined product identifiers.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to processing captured images. In some embodiments, there is provided a system for processing captured images of objects at a product storage facility including a trained machine learning model; and a control circuit. The control circuit may group a plurality of product identifiers into one or more clusters based on at least one of visual similarity of corresponding images, textual similarity of corresponding associated descriptions, and associated relationships between product identifiers of the plurality of product identifiers; determine clusters having common elements that are at least within a similarity threshold of each other; merge the clusters with the common elements; and generate a mapping dataset used to retrain the trained machine learning model to identify a plurality of objects. The mapping dataset may include a plurality of associations of associated product identifiers to a single object.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to processing captured images. In some embodiments, there is provided a system for processing captured images of objects at a product storage facility including a trained machine learning model stored in a memory; and a control circuit. The control circuit may obtain an image at the product storage facility; cluster objects depicted in the image that have same product identifiers into a corresponding group; determine coordinates of each bounding box of each clustered object in the corresponding group; determine a bounding box representative depth value of pixels inside the bounding box of each clustered object; determine an overall representative depth value of the corresponding group based on bounding box representative depth values of clustered objects; and exclude the clustered objects from identified objects in the image upon a determination that the overall representative depth value is greater than a threshold.

Abstract: Systems and methods of detecting support members of product storage structures that store products at a product storage facility include an image capture device that captures images of a product storage structure including vertical and horizontal support members. A computing device including a control circuit is configured to: obtain the images of the product storage structure captured by the image capture device, stitch the obtained images together to generate a stitched image that depicts the product storage structure, generate a color distribution map of the stitched image of the product storage structure to detect individual ones of the horizontal and vertical support members of the product storage structure.

Abstract: Systems and methods of creating reference template images for detecting and recognizing products at a product storage facility include an image capture device having a field of view that includes a product storage structure of the product storage facility, and a computing device including a control circuit and being communicatively coupled to the image capture device. The computing device obtains images of the product storage structure captured by the image capture device, analyzes the obtained images to detect individual ones of the products located on the product storage structure. Then, the computing device identifies the individual ones of the products detected in the images and crops each of the individual ones of the identified products from the images to generate cropped images. The computing device then creates a cluster of the cropped images, and selects one of the cropped images as a reference template image of an identified individual product.

Abstract: One example method involves generating a calibration control signal that causes an actuator to rotate a first platform at least one complete rotation about an axis. The method also involves receiving encoder output signals. The encoder output signals are indicative of angular positions of the first platform about the axis. The method also involves receiving sensor output signals from an orientation sensor mounted on the first platform. The sensor output signals are indicative of a rate of change to an orientation of the orientation sensor. The method also involves determining calibration data based on given sensor output signals received from the orientation sensor during the at least one complete rotation. The calibration data is for mapping the encoder output signals to calibrated measurements of the angular positions of the first platform about the axis.

Abstract: A method of updating a clock associated with an autonomous vehicle includes determining, at a processor, a sensor-based position of the autonomous vehicle. The sensor-based position is determined based on data from one or more sensors and based on a digital map accessible to the processor. The method also includes determining, at the processor, a global positioning system (GPS) computed position of the autonomous vehicle and a GPS time. The GPS computed position and the GPS time are determined based on a plurality of GPS signals received from GPS satellites. The method further includes comparing the sensor-based position to the GPS computed position to determine whether the sensor-based position is within a threshold distance from the GPS computed position. The method also includes updating the clock associated with the autonomous vehicle based on the GPS time in response to a determination that the sensor-based position is within the threshold distance from the GPS computed position.

Abstract: Systems and methods of verifying pairings of price tag labels and products at a product storage facility include an image capture device that moves about and captures images of product storage structures at the product storage facility, and a database that stores inventory data associated with the products stocked at the product storage facility. A computing device processes the images to extract one or more characters from the price tag labels and products detected in the images, correlates the extracted characters to the inventory data to identify a product code and a product name that matches the characters extracted from the price tag labels and the products. If the characters extracted from the price tag and from the on-shelf product to which the price tag label is allocated match, the database is updated to reflect that the price tag label is properly allocated to the appropriate on-shelf product.

Abstract: Systems and methods for extrinsic calibration of vehicle-mounted sensors are provided. One example method involves obtaining first sensor data collected by a first sensor and a second sensor while a vehicle is aligned in a first yaw direction. The method also involves obtaining second sensor data collected by the first sensor and the second sensor while the vehicle is aligned in a second yaw direction. The method also involves determining, based on the first sensor data and the second sensor data, (i) first pitch and roll misalignments of the first sensor relative to the vehicle and (ii) second pitch and roll misalignments of the second sensor relative to the first sensor. The method also involves determining third pitch and roll misalignments of the second sensor relative to the vehicle based on (i) the first pitch and roll misalignments and (ii) the second pitch and roll misalignments.

Abstract: One example method involves generating a calibration control signal that causes an actuator to rotate a first platform at least one complete rotation about an axis. The method also involves receiving encoder output signals. The encoder output signals are indicative of angular positions of the first platform about the axis. The method also involves receiving sensor output signals from an orientation sensor mounted on the first platform. The sensor output signals are indicative of a rate of change to an orientation of the orientation sensor. The method also involves determining calibration data based on given sensor output signals received from the orientation sensor during the at least one complete rotation. The calibration data is for mapping the encoder output signals to calibrated measurements of the angular positions of the first platform about the axis.

Abstract: Systems and methods of monitoring inventory of a product storage facility include an image capture device configured to move about the product storage areas of the product storage facility and capture images of the product storage areas from various angles. A computing device coupled to the image capture device obtains the images of the product storage areas captured by the image capture device and processes the obtained images of the product storage areas to detect individual products captured in the obtained images. Based on detection of the individual products captured in the images, the computing device analyzes each of the obtained images to detect one or more adjacent product storage structures (shelves, pallets, etc.) and identifies and selects a single image that fully shows a product storage structure of interest and fully shows each of the products stored on the product storage structure of interest.

Abstract: A method of manufacturing a pressure vessel (10) comprising the steps of dividing a wall (104) of a section (100) of the pressure vessel (10) into a first segment (120) and a second segment (150), separating the first segment (120) from the second segment (150), fitting apparatus (400) onto the first segment (120), and then re-attaching the first segment (120) and the second segment (150).

Abstract: Some embodiments provide retail product ordering systems comprising: a user computing device comprising an application executed by a device control circuit to: receive an audible utterance; controls a product identifier application interface to: apply a tokenizer model and obtain a set of individual search words; apply a series of featurizer models to the search words to generate features; and apply a classifier and extractor model based on the features and generate multiple requested product entities each comprising a respective sub-set of the position labeled product terms; wherein the device control circuit is further configured to access a purchase history database, confirm an accuracy of each of requested product entities relative to a purchase history, generate a listing of determined product identifiers corresponding to the confirmed set of the multiple requested product entities, and control a display system of the user computing device to render the listing of determined product identifiers.

Abstract: A method of manufacturing a pressure vessel (10) comprising the steps of dividing a wall (104) of a section (100) of the pressure vessel (10) into a first segment (120) and a second segment (150), separating the first segment (120) from the second segment (150), fitting apparatus (400) onto the first segment (120), and then re-attaching the first segment (120) and the second segment (150).

Abstract: Systems and methods for estimating sensor timestamps by oversampling are provided. One example method involves observing, at a sampling frequency, sensor data from a register of a sensor. The sensor updates the register with sensor data at as sensor update frequency. The sampling frequency is different from the sensor update frequency. The method also involves generating, based on the sensor update frequency and the sampling frequency, an observed sequence representing the sensor data. The observed sequence indicates whether the register is observed to be updated or not updated. The method also involves estimating, from the observed sequence, the sensor update frequency and a sensor update phase. The method also involves determining, based on the sensor update frequency as estimated and the sensor update phase as estimated, a timestamp corresponding to an update of the register.