Abstract: Described herein is a method comprising (a) sending unmanned aircraft system (UAS) data providing a first UAS location indication on a map on a display of the computing device, wherein the first UAS location indication comprises an aggregate indication of a plurality of UASs located within a first area on the map, (b) receiving data comprising a request for additional information related to the first UAS location indication, (c) in response to receiving the request for additional information, sending additional location data related to the plurality of UASs, including a plurality of second UAS location indications at a plurality of locations within the first area on the map, wherein each second UAS indication corresponds to a subset of the plurality of UASs represented by the first UAS location indication, and (d) updating the display of the computing device to show the plurality of second UAS location indications.

Abstract: A method for automated assignment of a staging pad to an unmanned aerial vehicle (UAV) includes: launching the UAV from a launch location; tracking a drift of the UAV from the launch location; determining a subsequent position of the UAV after the launching based upon geofiducial navigation; calculating an estimated position of the launch location by offsetting the subsequent position by the drift; attempting to match the estimated position to an available staging pad of a plurality of staging pads; and assigning the UAV to the available staging pad when the estimated position successfully matches to the available staging pad.

Abstract: An unmanned aerial vehicle (UAV) includes a fuselage, a pair of wings attached to the fuselage, and a propulsion system mounted to the wings to provide propulsion to the UAV. The fuselage has an outer fuselage shell that is a first mechanical support structure for an airframe of the UAV. The pair of wings is attached to the fuselage and shaped to provide aerodynamic lift. The wings have outer wing shells that are second mechanical support structures for the airframe. The outer fuselage shell or the outer wing shells comprise one or more formed-metal sheets.

Abstract: A technique for detecting an environmental change to a delivery zone via an unmanned aerial vehicle includes obtaining an anchor image and an evaluation image, each representative of the delivery zone, providing the anchor image and the evaluation image to a machine learning model to determine an embedding score associated with a distance between representations of the anchor image and the evaluation image within an embedding space, and determining an occurrence of the environmental change to the delivery zone when the embedding score is greater than a threshold value.

Abstract: A landing pad for an unmanned aerial vehicle (“UAV”) is disclosed. The landing pad includes a support structure, a charging pad, and a plurality of movable UAV supports. The charging pad is coupled to the support structure and able to move relative to the support structure. The UAV supports are also coupled to the support structure and configured to translate along the support structure from a first position to a second position. When the UAV supports are in the first position, the charging pad supports the UAV. When the UAV supports are in the second position, the charging pad is lowered and the UAV supports then provide support to the UAV.

Abstract: A drop test system includes support members offset from each other and having corresponding tracks, a lifting rod bridging the support members and having rod ends adapted to engage with the tracks to move along the tracks, and a pair of spiral cams adapted to rotate in unison and positioned to engage with and reciprocally lift and drop the lifting rod as the spiral cams rotate. The spiral cams each have a perimeter shape that includes an abrupt section and a curved section that connects to opposing ends of the abrupt section with a smooth curvature. The lifting rod is adapted to ride on the perimeter shape of the spiral cams and gradually lift and drop a unit under test (UUT) as the spiral cams rotate.

Abstract: A method includes determining an operational condition associated with an unmanned aerial vehicle (UAV). The method includes, responsive to determining the operational condition, causing the UAV to perform a pre-flight check. The pre-flight check includes hovering the UAV above a takeoff location. The pre-flight check includes, while hovering the UAV, moving one or more controllable components of the UAV in accordance with a predetermined sequence of movements. The pre-flight check includes obtaining, by one or more sensors of the UAV, sensor data indicative of a flight response of the UAV to moving the one or more controllable components while hovering the UAV. The pre-flight check includes comparing the sensor data to expected sensor data associated with an expected flight response to the predetermined sequence of movements while hovering the UAV. The pre-flight check includes, based on comparing the sensor data to the expected sensor data, evaluating performance of the UAV.

Abstract: In some embodiments, a computer-implemented method of managing a fleet of unmanned aerial vehicles (UAVs) is provided. A fleet management computing system receives telemetry information from a plurality of UAVs. The fleet management computing system generates a map interface having a plurality of UAV icons based on the telemetry information. The fleet management computing system receives a selection of an initial group of UAV icons via the map interface, wherein the initial group of UAV icons includes two or more UAV icons. The fleet management computing system receives a de-selection of one or more UAV icons from the initial group of UAV icons to create a final selected group of UAV icons. The fleet management computing system transmits a command to UAVs associated with the UAV icons of the final selected group of UAV icons.

Abstract: Described herein are methods and systems for motorized control of a tether, such as for purposes of user interaction and feedback. In particular, a UAV's control system may determine one or more operational parameters of a motor for a winch disposed in the UAV, the winch including the tether and a spool. The control system may then detect in the one or more operational parameters, an operational pattern of the motor that is indicative of an intentional user-interaction with the tether. Based on the detected operational pattern of the motor that is indicative of the intentional user-interaction with the tether, the control system may determine a motor response process. Then, the control system may operate the motor in accordance with the determined motor response process.

Abstract: A technique for operating unmanned aerial vehicles (UAVs) in a terminal area from which the UAVs are staged includes charging a plurality of the UAVs on charging pads disposed in a staging array at the terminal area. Merchant facilities for preparing packages for delivery by the UAVs are disposed about a periphery of the staging array. The UAVs are relocated under their own propulsion from interior charging pads to peripheral loading pads of the staging array as the peripheral loading pads become available and the UAVs are deemed sufficiently charged and ready for delivery missions.

Abstract: An unmanned aerial vehicle (UAV) includes a propulsion system, a global navigation satellite system (GNSS) sensor, a camera and a controller. The controller includes logic that, in response to execution by the controller, causes the UAV to in response to detecting a loss of tracking by the GNSS sensor determine an estimated location of the UAV on a map based on a location image captured by the camera, determine a route to a destination using tracking parameters embedded in the map, wherein the map is divided into a plurality of sections and the tracking parameters indicate an ease of determining a location of the UAV using images captured by the camera with respect to each section, and control the propulsion system to cause the UAV to follow the route to the destination.

Abstract: A modular housing structure for housing a plurality of unmanned aerial vehicles (UAVs) includes a plurality of housing segments and a plurality of landing pads. The plurality of housing segments are shaped to mechanically join together to define an interior of the modular housing structure. The individual housing segments have a common structural shape that repeats when assembled to form the modular housing structure. The plurality of landing pads are positioned within the individual housing segments, each of the landing pads sized to physically support and charge a corresponding one of the UAVs.

Abstract: A technique of operating an unmanned aerial vehicle (UAV) adapted for a package delivery mission includes: powering distributed propulsion units during takeoff and landing segments of the package delivery mission and idling at least a portion of the distributed propulsion units while powering a pair of outboard propulsion units during a cruise segment of the package delivery mission. The distributed propulsion units are mounted below fixed wings of the UAV and have first propellers mounted fore of the fixed wings. The outboard propulsion units are each mounted to a corresponding one of the fixed wings outboard of the distributed propulsion units. The outboard propulsion units include outboard propellers having a larger diameter than the first propellers.

Abstract: An example UAV landing structure includes a landing platform for a UAV, a cavity within the landing platform, and a track that runs along the landing platform and at least a part of the cavity. The UAV may include a winch system that includes a tether that may be coupled to a payload. Furthermore, the cavity may be aligned over a predetermined target location. The cavity may be sized to allow the winch system to pass a tethered payload through the cavity. The track may guide the UAV to a docked position over the cavity as the UAV moves along the landing platform. When the UAV is in the docked position, a payload may be loaded to or unloaded from the UAV through the cavity.

Abstract: Example implementations may relate to door-enabled loading and release of payloads in an unmanned aerial vehicle (UAV), which could be a type of UAV in a group of UAVs that is assigned to carry out certain transport tasks. In particular, the UAV may include a fuselage having a first side and a second side, as well as a chamber formed within the fuselage and arranged to house a payload. A first door may be arranged on the first side of the fuselage, such that an opening of the first door enables loading of the payload into the chamber. And a second door may be arranged on the second side of the fuselage, such that an opening of the second door enables release of the payload from the chamber. Moreover, the UAV may include a control system configured to control flight of the UAV, and possibly opening and/or closing of door(s).

Abstract: An example method of manufacturing a wing includes providing a wing frame. The wing frame includes a primary spar, a drag spar, a plurality of transverse frame elements having at least one spar joiner, and a plurality of mounting elements. The primary spar is coupled to the drag spar via the at least one spar joiner. The method further includes placing the wing frame into a mold, wherein the mold defines a shape of the wing. The method also includes injecting the mold with an air-filled matrix material, such that the air-filled matrix material substantially encases the wing frame and fills the defined shape of the wing, and such that the plurality of transverse frame elements provide torsional rigidity to the wing.

Abstract: In some embodiments, techniques are provided for verifying operability of an automatic dependent surveillance-broadcast (ADS-B) receiver included in a first unmanned aerial vehicle (UAV), which includes receiving ADS-B data representative of ADS-B messages broadcast by traffic within a reception range of the ADS-B receiver during a first period of time, estimating a traffic environment for a service area spanning, at least in part, a first operating area of the first UAV during the first period of time, determining an expected observed traffic of the first UAV during the first period of time based on the estimated traffic environment, and verifying operability of the ADS-B receiver of the first UAV based on a comparison between the expected observed traffic of the first UAV and the traffic associated with the ADS-B data received by the ADS-B receiver of the first UAV.

Abstract: A method includes determining a threshold capacity associated with at least a first unmanned aerial vehicle (UAV) and a second UAV. The method includes initially setting a target charge voltage of a first battery of the first UAV to less than a full charge voltage to limit a state of charge of the first battery based on the threshold capacity. The method includes, over a lifetime of the first battery of the first UAV, periodically comparing a full charge capacity of the first battery to the threshold capacity. The method includes, based on the comparing, periodically adjusting the target charge voltage of the first battery, such that, as the full charge capacity of the first battery decreases with age, the target charge voltage increases towards the full charge voltage of the first battery.

Abstract: An unmanned aerial vehicle (UAV) is disclosed that includes a retractable payload delivery system. The payload delivery system can lower a payload to the ground using a delivery device that secures the payload during descent and releases the payload upon reaching the ground. The location of the delivery device can be determined as it is lowered to the ground using image tracking. The UAV can include an imaging system that captures image data of the suspended delivery device and identifies image coordinates of the delivery device, and the image coordinates can then be mapped to a location. The UAV may also be configured to account for any deviations from a planned path of descent in real time to effect accurate delivery locations of released payloads.

Abstract: In some embodiments, techniques are provided for analyzing time series data to detect anomalies. In some embodiments, the time series data is processed using a machine learning model. In some embodiments, the machine learning model is trained in an unsupervised manner on large amounts of previous time series data, thus allowing highly accurate models to be created from novel data. In some embodiments, training of the machine learning model alternates between a fitting optimization and a trimming optimization to allow large amounts of training data that includes untagged anomalous records to be processed. Because a machine learning model is used, anomalies can be detected within complex systems, including but not limited to autonomous vehicles such as unmanned aerial vehicles. When anomalies are detected, commands can be transmitted to the monitored system (such as an autonomous vehicle) to respond to the anomaly.