A technique for localization of an unmanned aerial vehicle (UAV) includes: acquiring aerial images of a terrain below the UAV with an onboard camera system of the UAV while the UAV is flying a mission along a preplanned route over the terrain; generating a current optical flow map based upon image pixel motion between consecutive images in a sequence of the aerial images; comparing the current optical flow map to reference optical flow maps stored onboard the UAV, wherein the reference optical flow maps are precomputed from a model of the terrain along the preplanned route; and determining a position in at least two lateral dimensions based on the comparing.
2.
USING ASSET MAPS TO INFORM REAL-TIME MACHINE LEARNING MODELS FOR UAV NAVIGATION
A technique for informing navigation of a UAV includes storing an asset map of a ground area, wherein the asset map includes a reference aerial image of the ground area annotated with labels describing reference objects depicted in the reference aerial image; acquiring a current aerial image of the ground area with an onboard camera system of the UAV while the UAV is flying above the ground area; mapping correspondences between the reference aerial image and the current aerial image using a homography estimating tool executing onboard the UAV; analyzing the current aerial image with an object detection model to detect a first object positioned at the ground area; and validating or informing a detection of the first object by the object detection model based on the mapping of the correspondences.
3.
REWEIGH MANEUVER FOR ACCURATE PAYLOAD MASS ESTIMATION
A method includes causing an aerial vehicle to retract, to within a first distance of the aerial vehicle, a payload that is coupled to the aerial vehicle by a tether. The method also includes causing the aerial vehicle to lower the payload from the aerial vehicle by at least a second distance. The method additionally includes obtaining data indicative of a force applied to the tether by the payload, while the payload is lowered from the aerial vehicle, and determining a mass of the payload based on the data indicative of the force applied to the tether by the pay load. The method further includes determining, based on the mass of the payload, a maneuver to be performed with the payload by the aerial vehicle, and causing the aerial vehicle to perform the maneuver.
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
4.
Reweigh Maneuver for Accurate Payload Mass Estimation
A method includes causing an aerial vehicle to retract, to within a first distance of the aerial vehicle, a payload that is coupled to the aerial vehicle by a tether. The method also includes causing the aerial vehicle to lower the payload from the aerial vehicle by at least a second distance. The method additionally includes obtaining data indicative of a force applied to the tether by the payload while the payload is lowered from the aerial vehicle, and determining a mass of the payload based on the data indicative of the force applied to the tether by the payload. The method further includes determining, based on the mass of the payload, a maneuver to be performed with the payload by the aerial vehicle, and causing the aerial vehicle to perform the maneuver.
B64D 1/22 - Taking-up articles from earth's surface
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
B66C 13/06 - Auxiliary devices for controlling movements of suspended loads, or for preventing cable slack for minimising or preventing longitudinal or transverse swinging of loads
B66C 13/16 - Applications of indicating, registering, or weighing devices
5.
USING A REPRODUCIBLE REAL-TIME PROCESSING GRAPH FOR AUTONOMOUS VEHICLE OPERATIONS
In some embodiments, a computer-implemented method of generating perception commands is provided. A simulation computing system determines delay prediction information for a perception system. The delay prediction information is usable to predict an amount of delay for an autonomous vehicle computing system to generate perception commands using an in-flight perception graph. The simulation computing system obtains perception data, and provides the perception data to a simulation perception graph to generate a perception command. The perception command includes a timestamp and an indication of one or more types of perception data used by the simulation perception graph to generate the command. The simulation computing system determines a predicted delay for the perception command based on the delay prediction information. The simulation computing system updates the timestamp of the perception command based on the predicted delay. The simulation computing system provides the perception command and the predicted delay to a simulation queue.
A package coupling apparatus for securing a package to an unmanned aerial vehicle (UAV) is provided. The package coupling apparatus includes a support plate configured to be secured to an upper surface of the package and a handle extending up from the support plate. The handle includes a handle opening and a bridge that extends over the handle opening, wherein the bridge is configured to be secured by a component of the UAV.
B66C 1/10 - Load-engaging elements or devices attached to lifting, lowering, or hauling gear of cranes, or adapted for connection therewith for transmitting forces to articles or groups of articles by mechanical means
B64D 1/22 - Taking-up articles from earth's surface
B64U 101/66 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval for retrieving parcels
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
A package adapted for use with an uncrewed aerial vehicle (UAV) is provided. The package includes a container with a bottom face including a first perimeter formed by eight edges, a closable top opposite the bottom face, the closeable top including a second perimeter formed by four edges, and a side wall extending between the bottom face and the closable top. The side wall includes a front face, a rear face, two lateral faces, front angled sections between the front face and the lateral faces, and rear angled sections between the rear face and the lateral faces. The package also includes a hanger secured to the closable top of the container. The hanger includes a handle having a handle opening and a bridge that extends over the handle opening. The bridge is configured to be secured by a component of the UAV.
B65D 25/22 - External fittings for facilitating lifting or suspending of containers
B64D 1/22 - Taking-up articles from earth's surface
B65D 5/20 - Rigid or semi-rigid containers of polygonal cross-section, e.g. boxes, cartons or trays, formed by folding or erecting one or more blanks made of paper by folding-up portions connected to a central panel from all sides to form a container body, e.g. of tray-like form
A package adapted for use with an uncrewed aerial vehicle (UAV) is provided. The package includes a container with a bottom face including a first perimeter formed by eight edges, a closable top opposite the bottom face, the closeable top including a second perimeter formed by four edges, and a side wall extending between the bottom face and the closable top. The side wall includes a front face, a rear face, two lateral faces, front angled sections between the front face and the lateral faces, and rear angled sections between the rear face and the lateral faces. The package also includes a hanger secured to the closable top of the container. The hanger includes a handle having a handle opening and a bridge that extends over the handle opening. The bridge is configured to be secured by a component of the UAV.
B65D 88/14 - Large containers rigid specially adapted for transport by air
B65D 25/22 - External fittings for facilitating lifting or suspending of containers
B64D 1/22 - Taking-up articles from earth's surface
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
9.
SIDE-TO-TOP IMAGE MAPPING FOR RAPID DEPLOYMENT OF UAS GROUND ASSETS
A technique for mapping assets deployed for an unmanned aerial vehicle (UAV) service includes capturing, with a mobile computing device, a plurality of side view images of a ground area including the assets, the assets deployed to the ground area for supporting operations of the UAV service, the side view images acquired from different pedestrian vantage points about the ground area; measuring, by the mobile computing device, camera locations of the mobile computing device when capturing the side view images; analyzing the side view images along with the camera locations of the mobile computing device to determine asset locations of the assets at the ground area; and updating a backend management system of the UAV service to record the asset locations determined from the analyzing.
G05D 1/00 - Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
G05D 1/243 - Means capturing signals occurring naturally from the environment, e.g. ambient optical, acoustic, gravitational or magnetic signals
G05D 1/247 - Arrangements for determining position or orientation using signals provided by artificial sources external to the vehicle, e.g. navigation beacons
G05D 1/248 - Arrangements for determining position or orientation using signals provided by artificial sources external to the vehicle, e.g. navigation beacons generated by satellites, e.g. GPS
G05D 1/249 - Arrangements for determining position or orientation using signals provided by artificial sources external to the vehicle, e.g. navigation beacons from positioning sensors located off-board the vehicle, e.g. from cameras
In one aspect, a payload retrieval system is provided. The payload retrieval system includes a retriever guide that forms a channel having an inlet end and an exit end. The retriever guide is adapted to receive a payload retriever at the inlet end of the channel and direct the payload retriever to the exit end of the channel. The payload retrieval system includes a payload holder disposed at the exit end of the channel and configured to hold a handle of a payload, and includes a payload support brace disposed below the payload holder. The payload support brace includes first and second portions that are spaced apart to form an open payload storage area that is below the payload holder and between the first and second portions, and is configured to support larger payloads so as to position the larger payloads at an angle when held on the payload holder.
B64F 1/32 - Ground or aircraft-carrier-deck installations for handling freight
B64D 1/22 - Taking-up articles from earth's surface
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
11.
SIDE-TO-TOP IMAGE MAPPING FOR RAPID DEPLOYMENT OF UAS GROUND ASSETS
A technique for mapping assets deployed for an unmanned aerial vehicle (UAV) service includes capturing, with a mobile computing device, a plurality of side view images of a ground area including the assets, the assets deployed to the ground area for supporting operations of the UAV service, the side view images acquired from different pedestrian vantage points about the ground area; measuring, by the mobile computing device, camera locations of the mobile computing device when capturing the side view images; analyzing the side view images along with the camera locations of the mobile computing device to determine asset locations of the assets at the ground area; and updating a backend management system of the UAV service to record the asset locations determined from the analyzing.
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G06V 20/17 - Terrestrial scenes taken from planes or by drones
A visual monitoring system for monitoring an autonomous flight operational area from a remote location is provided. The visual monitoring system can be configured to capture image data related to a verification target with one or more cameras, transmit the image data to a remote location, and display the image data related to the verification target for review by operational personnel at the remote location. The image data can be related to at least a first verification target having a first nominal condition. The operational personnel can review the image data and compare it to the data to the first nominal condition. If an off-nominal condition of the first verification target is detected by the operational personnel, the visual monitoring system can pause operations at the autonomous flight operational area until the off-nominal condition of the first verification target is resolved.
A method for perception validation of an aerial vehicle includes: acquiring an image of a ground area with an onboard camera system of the aerial vehicle, generating an above ground altitude (AGL) estimate with a neural network trained to output the AGL estimate in response to the image fed as an input to the neural network, generating a motion estimate or a position estimate based upon sensor data output from a sensor disposed onboard the aerial vehicle, and cross-validating the motion or position estimate against the AGL estimate.
A technique for provisioning UAVs to operate in a specific geographical region includes acquiring reference aerial images of the specific geographical region from a secondary source. The reference aerial images have at least one style characteristic that is distinct from that of operational aerial images acquired by the UAVs during operation. The reference aerial images are transformed into training images that adopt a style of the operational aerial images using a neural style transfer. A neural network that facilitates vision-based navigation of the UAVs is trained using the training images. The neural network is trained to operate in the specific geographical region prior to operation in the specific geographical region.
A technique for informing navigation of a UAV includes storing an asset map of a ground area, wherein the asset map includes a reference aerial image of the ground area annotated with labels describing reference objects depicted in the reference aerial image; acquiring a current aerial image of the ground area with an onboard camera system of the UAV while the UAV is flying above the ground area; mapping correspondences between the reference aerial image and the current aerial image using a homography estimating tool executing onboard the UAV; analyzing the current aerial image with an object detection model to detect a first object positioned at the ground area; and validating or informing a detection of the first object by the object detection model based on the mapping of the correspondences.
In some embodiments, a computer-implemented method of communicating sensor data between an autonomous vehicle computing system and a remote computing system is provided. The autonomous vehicle computing system gathers sensor data generated by at least one sensor of the autonomous vehicle computing system. The autonomous vehicle computing system determines an amount of available bandwidth between the autonomous vehicle computing system and the remote computing system. The autonomous vehicle computing system retrieves a local portion of a split machine learning model corresponding to the amount of available bandwidth from a model data store. The autonomous vehicle computing system processes the sensor data using the local portion to produce an intermediate result. The autonomous vehicle computing system transmits the intermediate result to the remote computing system for processing of the intermediate result using a remote portion of the split machine learning model.
In some embodiments, a computer-implemented method of communicating sensor data between an autonomous vehicle computing system and a remote computing system is provided. The autonomous vehicle computing system gathers sensor data generated by at least one sensor of the autonomous vehicle computing system. The autonomous vehicle computing system determines an amount of available bandwidth between the autonomous vehicle computing system and the remote computing system. The autonomous vehicle computing system retrieves a local portion of a split machine learning model corresponding to the amount of available bandwidth from a model data store. The autonomous vehicle computing system processes the sensor data using the local portion to produce an intermediate result. The autonomous vehicle computing system transmits the intermediate result to the remote computing system for processing of the intermediate result using a remote portion of the split machine learning model.
A method includes receiving an input specifying a starting location and a destination location for an aerial vehicle. The method additionally includes determining, based on the starting location and the destination location, an aerial path for the aerial vehicle to follow from the starting location to the destination location. The method also includes determining, based on the aerial path, a property of aerial image data, where the aerial image data is obtainable using the aerial vehicle while traversing the aerial path, and where the aerial image data represents an environment along the aerial path. The method further includes determining, based on the property, a path score associated with the aerial path, and outputting the aerial path based on the path score.
An unmanned aerial vehicle (UAV) includes a fuselage including a front, a rear, a top, a bottom, and an open cargo bay with a lower access opening in the bottom of the fuselage. An aerodynamic device is positioned on a surface of the bottom of the fuselage in front of the open cargo bay. A coupler is configured to secure a payload at the top of the open cargo bay.
B64U 101/60 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons
20.
USING NeRF MODELS TO FACILITATE OPERATIONS OF A UAV DELIVERY SERVICE
A technique for maintaining a terrain model includes: acquiring aerial images of a scene at an area of interest (AOI), wherein the aerial images are acquired by a UAV during a flight mission of the UAV that passes over the AOI; training a ML model onboard the UAV with one or more of the aerial images, wherein the ML model comprises a neural network, which after the training, encodes a volumetric representation of the scene; determining whether the terrain model of the AOI is deemed out-of-date based upon whether the training results in greater than a threshold change in the ML model; and uploading image data acquired by the UAV during the flight mission to a backend data system in response to determining that the terrain model is deemed out-of-date, wherein the image data includes, or is derived from, at least a portion of the aerial images.
A technique for localizing utility lines includes capturing aerial images of a ground area below a UAV; recording a position of the UAV when capturing the aerial images; detecting a presence of an object in the aerial images suspected to be a utility line; identifying two offset pixel points in each of the aerial images that coincide with the object in each aerial image; converting the two offset pixel points in each of the aerial images to a world frame; defining a plurality of geometric planes in the world frame each corresponding to one the aerial images, wherein the each of the geometric planes is defined by the position of the UAV when capturing a corresponding to one of the aerial images and the two offset pixel points in the world frame corresponding to the one of the aerial images; and determining an intersection approximation of the geometric planes.
A technique for localizing utility lines includes capturing aerial images of a ground area below a UAV; recording a position of the UAV when capturing the aerial images; detecting a presence of an object in the aerial images suspected to be a utility line; identifying two offset pixel points in each of the aerial images that coincide with the object in each aerial image; converting the two offset pixel points in each of the aerial images to a world frame; defining a plurality of geometric planes in the world frame each corresponding to one the aerial images, wherein the each of the geometric planes is defined by the position of the UAV when capturing a corresponding to one of the aerial images and the two offset pixel points in the world frame corresponding to the one of the aerial images; and determining an intersection approximation of the geometric planes.
An unmanned aerial vehicle fleet management system initiates creation of a digital airspace area of operation, presents in a user interface an area classifier selection field configured to select from a set of available area classifiers; receives first user input classifying the digital airspace area of operation as an oversight area; presents a ruleset selection field; receives second user input specifying one or more rulesets of the oversight area; creates the oversight area based at least in part on the first and second inputs; and creates a pilot area associated with the oversight area that inherits the specified ruleset(s) of the oversight area. The oversight area and pilot area define areas of operation of different types for different classes of users, such as pilots and flight operations managers. The specified ruleset(s) comprise rules related to flight approvals. Flight missions can be created or altered based on the specified ruleset(s).
A joiner includes a first and second portions configured to mount to respective first and second structural members. Each of the first and second portions includes a body with a receiving surface to receive the respective structural member. The first portion includes a group of first coupling structures disposed on the first body and the second portion includes a group of second coupling structures disposed on the second body. The first coupling structures are configured to mate with the second coupling structures such that engagement surfaces of the first coupling structures engage engagement surfaces of the second coupling structures so as to transfer loads between the second portion and first portion and to limit relative movement between the first portion and second portion with respect to the first direction and with respect to a vertical direction.
B64U 30/29 - Constructional aspects of rotors or rotor supportsArrangements thereof
B64U 101/64 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval
A method includes securing a payload on a payload retriever, where the payload retriever is attached to a tether that extends from an uncrewed aerial vehicle (UAV). The method also includes retracting the tether to position the payload retriever at a first location, and securing the payload to a releasable coupler of the UAV. The method also includes further retracting the tether to move the payload retriever from the first location and disengage the payload retriever from the payload. Further, the method includes actuating the releasable coupler to release the payload from the UAV.
B64D 1/22 - Taking-up articles from earth's surface
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
A method includes determining, by an unmanned aerial vehicle (UAV), a position of an autoloader device for the UAV; based on the determined position of the autoloader device, causing the UAV to follow a descent trajectory in which the UAV moves from a starting position to a first nudged position in order to deploy a tethered pickup component of the UAV to a payout position on an approach side of the autoloader device; deploying the tethered pickup component of the UAV to the payout position; causing the UAV to follow a side-step trajectory in which the UAV moves laterally to a second nudged position in order to cause the tethered pickup component of the UAV to engage the autoloader device; and retracting the tethered pickup component of the UAV to pick up a payload from the autoloader device.
B64U 101/30 - UAVs specially adapted for particular uses or applications for imaging, photography or videography
B64U 101/66 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval for retrieving parcels
In one aspect an uncrewed aerial vehicle (UAV) is provided. The uncrewed aerial vehicle includes a fuselage and a drag reduction device. The fuselage has a front end, a rear end, a top, and a bottom. The drag reduction device includes a proximal end and a distal end. The proximal end of the drag reduction device is coupled to the bottom of the fuselage. The drag reduction device is rotatable between a rest position and an active position in which the drag reduction device extends downward. A standoff is disposed on a rear side of the drag reduction device and is configured to engage a payload secured under the fuselage and hold the drag reduction device at a distance from the payload when the drag reduction device is in the active position.
B64U 101/64 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval
B64C 7/00 - Structures or fairings not otherwise provided for
B64C 21/08 - Influencing air flow over aircraft surfaces by affecting boundary layer flow by use of slot, ducts, porous areas or the like adjustable
A method is disclosed. The method includes receiving an indication of presence of an aircraft in a vicinity of an uncrewed aerial vehicle (UAV) which is flying along a flight path. The method also includes decelerating, based on the received indication, the UAV to reduce a ground speed along the flight path. The method additionally includes descending, after reducing the ground speed, the UAV to a hover position. The method further includes determining, while the UAV is in the hover position, whether to resume the flight path or to land the UAV based on a determination of continued presence of the aircraft in the vicinity of the UAV. The method also includes controlling the UAV based on the determination of whether to resume the flight path or to land the UAV.
An uncrewed aerial vehicle (UAV) which includes a payload coupling apparatus secured to a tether. The payload coupling apparatus is configured to engage a payload. The UAV also includes a winch system configured to extend the tether for lowering the payload on the payload coupling apparatus during a delivery. The UAV also includes a payload latch movable between an open position and a closed position, wherein the payload latch is configured to secure the payload at the UAV when in the closed position and release the payload when in the open position.
B64U 50/38 - Charging when not in flight by wireless transmission
B64U 101/30 - UAVs specially adapted for particular uses or applications for imaging, photography or videography
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
A technique for managing an unplanned contingency landing of a unmanned aerial vehicle (UAV) includes determining by the UAV that the unplanned contingency landing is imminent, capturing aerial images of a ground area below the UAV with an onboard camera system as the UAV descends towards the ground area, semantically analyzing the aerial images to classify objects at the ground area into object classifications, depth analyzing the aerial images to determine above ground level (AGL) heights associated with each of the objects at the ground area, selecting a preferred landing site for the unplanned contingency landing that is coincident with one of the objects at the ground area based upon a contingency landing policy that ranks contingency landing sites based upon a combination of the object classifications and the AGL heights; and nudging the UAV towards the preferred landing site as the UAV descends towards the ground.
G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
G06V 20/17 - Terrestrial scenes taken from planes or by drones
31.
Payload Retriever Having Multiple Slots For Use with a UAV
A payload coupling apparatus having a housing comprising an outer surface extending around a perimeter of the housing, an upper portion above the outer surface and including a tether attachment point, and a lower portion below the outer surface; a first slot extending into the outer surface of the housing thereby forming a first lower lip on the housing beneath the first slot; wherein the first slot is adapted to receive a handle of a payload; and a second slot extending into the outer surface of the housing thereby forming a second lower lip on the housing beneath the second slot; wherein the second slot is adapted to receive the handle of the payload.
B64D 1/22 - Taking-up articles from earth's surface
B64F 1/32 - Ground or aircraft-carrier-deck installations for handling freight
B64U 101/66 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval for retrieving parcels
A technique for managing an unplanned contingency landing of a unmanned aerial vehicle (UAV) includes determining by the UAV that the unplanned contingency landing is imminent, capturing aerial images of a ground area below the UAV with an onboard camera system as the UAV descends towards the ground area, semantically analyzing the aerial images to classify objects at the ground area into object classifications, depth analyzing the aerial images to determine above ground level (AGL) heights associated with each of the objects at the ground area, selecting a preferred landing site for the unplanned contingency landing that is coincident with one of the objects at the ground area based upon a contingency landing policy that ranks contingency landing sites based upon a combination of the object classifications and the AGL heights; and nudging the UAV towards the preferred landing site as the UAV descends towards the ground.
A method includes charging a battery of a vehicle to a charge threshold voltage. The method also includes discharging the battery from the charge threshold voltage to a post-task voltage by performing a travel task using the vehicle. The method additionally includes determining that a battery calibration condition has been met. The method further includes, based on determining that the battery calibration condition has been met, discharging the battery from the post-task voltage to a discharge threshold voltage by performing a battery discharge task. The method yet further includes determining a capacity of the battery based on a first electrical output of the battery during the travel task and a second electrical output of the battery during the battery discharge task.
B60L 58/10 - Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
B64U 50/30 - Supply or distribution of electrical power
A technique for localization of an unmanned aerial vehicle (UAV) includes: acquiring aerial images of a terrain below the UAV with an onboard camera system of the UAV while the UAV is flying a mission along a preplanned route over the terrain; generating a current optical flow map based upon image pixel motion between consecutive images in a sequence of the aerial images; comparing the current optical flow map to reference optical flow maps stored onboard the UAV, wherein the reference optical flow maps are precomputed from a model of the terrain along the preplanned route; and determining a position in at least two lateral dimensions based on the comparing.
A payload retrieval apparatus including a stand having an upper end and a lower end, a channel having a first end and a second end, the channel coupled to the stand, a first extension that extends in a first direction from the first end of the channel, wherein the first extension is configured to direct a tether extending from a UAV and a payload retriever attached to an end of the tether toward the first end of the channel, wherein the second end of the channel has a payload engaging member positioned near the second end of the channel that is adapted to secure a payload, and wherein the payload retrieval apparatus is configured to cause the UAV to pick up the payload with the payload retriever while maintaining flying.
B64D 1/22 - Taking-up articles from earth's surface
B64C 39/02 - Aircraft not otherwise provided for characterised by special use
B64F 1/32 - Ground or aircraft-carrier-deck installations for handling freight
B64U 101/66 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval for retrieving parcels
B66C 1/04 - Load-engaging elements or devices attached to lifting, lowering, or hauling gear of cranes, or adapted for connection therewith for transmitting forces to articles or groups of articles by magnetic means
A method for unmanned aerial vehicle (UAV) mission planning includes acquiring a target aerial image of a geographic area representative of the geographic area illuminated by one or more artificial light sources, identifying a location of the one or more artificial light sources based on the target aerial image, rendering a simulated aerial image representative of the geographic area illuminated by the one or more artificial light sources at night using a digital surface model of the geographic area, the location of the one or more artificial light sources, and an irradiance parameter for the one or more artificial light sources, identifying one or more regions within the geographic area as having sufficient lighting for UAV operation at night based on the simulated aerial image, and generating a mission plan for the UAV based on the one or more regions within the geographic area.
A method for unmanned aerial vehicle (UAV) mission planning includes acquiring a target aerial image of a geographic area representative of the geographic area illuminated by one or more artificial light sources, identifying a location of the one or more artificial light sources based on the target aerial image, rendering a simulated aerial image representative of the geographic area illuminated by the one or more artificial light sources at night using a digital surface model of the geographic area, the location of the one or more artificial light sources, and an irradiance parameter for the one or more artificial light sources, identifying one or more regions within the geographic area as having sufficient lighting for UAV operation at night based on the simulated aerial image, and generating a mission plan for the UAV based on the one or more regions within the geographic area.
G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
G06V 10/60 - Extraction of image or video features relating to illumination properties, e.g. using a reflectance or lighting model
G06V 20/17 - Terrestrial scenes taken from planes or by drones
A method includes determining a portion of a flight path of an aerial vehicle. The method also includes determining an attribute value representing an operating condition expected to be experienced by the aerial vehicle at the portion of the flight path. The method additionally includes determining, based on the attribute value and using a non-linear model, a power value representing an amount of power expected to be consumed by the aerial vehicle in connection with the portion of the flight path. The method further includes determining, based on the power value, an energy value representing an amount of energy expected to be consumed by the aerial vehicle in connection with the portion of the flight path. The method yet further includes determining the flight path based on the energy value.
A method includes determining a portion of a flight path of an aerial vehicle. The method also includes determining an attribute value representing an operating condition expected to be experienced by the aerial vehicle at the portion of the flight path. The method additionally includes determining, based on the attribute value and using a non-linear model, a power value representing an amount of power expected to be consumed by the aerial vehicle in connection with the portion of the flight path. The method further includes determining, based on the power value, an energy value representing an amount of energy expected to be consumed by the aerial vehicle in connection with the portion of the flight path. The method yet further includes determining the flight path based on the energy value.
G05D 1/644 - Optimisation of travel parameters, e.g. of energy consumption, journey time or distance
G05D 101/15 - Details of software or hardware architectures used for the control of position using artificial intelligence [AI] techniques using machine learning, e.g. neural networks
A technique for processing delivery aborts by a UAV delivery service includes: acquiring a delivery zone (DZ) image of a delivery destination including a DZ for a package being delivered to the delivery destination by a UAV; determining to abort a delivery mission for the package based upon the DZ image; converting the DZ image to a vector embedding; performing a similarity search on a vector database using the vector embedding, the vector database storing reference images of other delivery destinations indexed to reference vector embeddings and outcome attributes describing delivery outcomes associated with the reference images, and wherein the similarity search identifies a subset of the reference images deemed to have a threshold similarity to the DZ image; and prompting a vision language model with the DZ image and the subset of the reference images to provide an abort explanation or to determine a delivery disposition for the DZ.
In one aspect an uncrewed aerial vehicle (UAV) is provided. The uncrewed aerial vehicle includes a fuselage and a drag reduction device. The fuselage has a front end, a rear end, a top, and a bottom. The drag reduction device includes a proximal end and a distal end. The proximal end of the drag reduction device is coupled to the bottom of the fuselage. The drag reduction device is rotatable between a rest position and an active position in which the drag reduction device extends downward. A standoff is disposed on a rear side of the drag reduction device and is configured to engage a payload secured under the fuselage and hold the drag reduction device at a distance from the payload when the drag reduction device is in the active position.
B64U 101/64 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval
A technique for processing delivery aborts by a UAV delivery service includes: acquiring a delivery zone (DZ) image of a delivery destination including a DZ for a package being delivered to the delivery destination by a UAV; determining to abort a delivery mission for the package based upon the DZ image; converting the DZ image to a vector embedding; performing a similarity search on a vector database using the vector embedding, the vector database storing reference images of other delivery destinations indexed to reference vector embeddings and outcome attributes describing delivery outcomes associated with the reference images, and wherein the similarity search identifies a subset of the reference images deemed to have a threshold similarity to the DZ image; and prompting a vision language model with the DZ image and the subset of the reference images to provide an abort explanation or to determine a delivery disposition for the DZ.
G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/17 - Terrestrial scenes taken from planes or by drones
43.
Dynamic UAV Transport Tasks for Pickup and Delivery of Packages
Example implementations relate to a method of dynamically updating a transport task of a UAV. The method includes receiving, at a transport-provider computing system, an item provider request for transportation of a plurality of packages from a loading location at a given future time. The method also includes assigning, by the transport-provider computing system, a respective transport task to each of a plurality of UAVs, where the respective transport task comprises an instruction to deploy to the loading location to pick up one or more of the plurality of packages. Further, the method includes identifying, by the transport-provider system, a first package while or after a first UAV picks up the first package. Yet further, the method includes based on the identifying of the first package, providing, by the transport-provider system, a task update to the first UAV to update the respective transport task of the first UAV.
B64U 101/60 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
44.
Drag reduction device for externally carried payloads on aircraft
An uncrewed aerial vehicle (UAV) includes a fuselage extending along a first direction from a rear end to a front end. The fuselage has a cross-sectional area at an intermediate position between the front and rear end. An external payload storage area is positioned at the intermediate position and is configured to receive a payload that is secured to the fuselage and that extends laterally outward from the cross-sectional area of the fuselage. A drag reduction device is coupled to the fuselage. The drag reduction device has a length extending from a free end to an attached end that is secured to the fuselage, a width that extends perpendicular to the first direction of the fuselage, and a depth. In an operating position, the drag reduction device is positioned in front of the payload storage area, is spaced from the payload storage area, and extends outward from the fuselage.
An uncrewed aerial vehicle (UAV) includes a support extending along a flight direction of the UAV. The support includes an elongate structural member, a cap coupled to a front end of the elongate structural member, and an energy absorber. The support extends along an axis that runs through the support from a front end to a rear end. The cap is coupled to the front end of the elongate structural member. The cap includes a support platform that has a front surface opposite the elongate structural member and that extends outward from the axis. The energy absorber is disposed on the front surface of the support platform and includes a crushable material configured to absorb energy under impact. The UAV also includes a first propeller unit coupled to the support.
A UAV having a fuselage body including a cavity that forms a cargo bay for transporting a payload, and a lower access opening providing an exit for the payload from the cargo bay, the lower access opening including a lower cargo bay door, an actuator positioned in the fuselage body, a linkage assembly connected to the actuator and connected to the lower cargo bay door, wherein the actuator and linkage assembly are operable to open and/or close the lower cargo bay door.
09 - Scientific and electric apparatus and instruments
12 - Land, air and water vehicles; parts of land vehicles
35 - Advertising and business services
39 - Transport, packaging, storage and travel services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable software for browsing and purchasing consumer
goods for delivery; navigation apparatus for autonomous
aircrafts and drones; downloadable software for operating,
maintaining, monitoring, logging, and navigating drones and
autonomous aircraft. Drones; autonomous aircraft; unmanned aerial vehicles
(UAVs). Business management of logistics for others; business
management of logistics in the field of drone delivery,
retail, delivery, and transportation; business advisory
services in the field of transportation logistics. Transportation and delivery services of goods by air;
management of autonomous aircraft and drone navigation in
the nature of traffic flow through advanced communications
network and technology; routing of autonomous aircraft and
drones by computer on data networks; aeronautic navigation
services, namely, aeronautic radio navigation services;
expedited shipping service of goods for others; GPS
navigation services for autonomous aircrafts and drones; air
navigation services for autonomous aircrafts and drones;
storage of goods; storage of goods for later pickup and
delivery purposes; storage of goods at designated pickup
locations; transportation logistics services, namely,
arranging, planning, and scheduling the delivery of goods by
drone for others. Providing on-line non-downloadable software for browsing and
purchasing consumer goods for delivery; software as a
service (SAAS) services featuring software for browsing and
purchasing consumer goods for delivery; providing on-line
non-downloadable software for operating, maintaining,
monitoring, logging, and navigating drones and autonomous
aircraft; software as a service (SAAS) services featuring
software for operating, maintaining, monitoring, logging,
and navigating drones and autonomous aircraft.
48.
METHODS AND SYSTEMS FOR DEEP STALL CONTROL OF UNCREWED AERIAL VEHICLES
Examples relate to uncrewed aerial vehicles (UAVs) and methods for controlled descent during control tier failures. A computing device may initially detect a control tier failure at an UAV. In some examples, the UAV includes a fuselage, a pair of wings extending outwardly from the fuselage, and a pair of stabilizers arranged in a V-shape configuration. Each stabilizer has a control surface that is adjustable relative to a fixed portion of the stabilizer. Based on detecting the control tier failure at the UAV, the computing device may adjust the control surface of each stabilizer from a. first angle to a. second angle relative to the fixed portion of the stabilizer. By adjusting the angle between the control surfaces and fixed portions of one or both stabilizers, the UAV may induce a deep stall maneuver that can enable a controlled descent of the UAV.
B64U 40/10 - On-board mechanical arrangements for adjusting control surfaces or rotorsOn-board mechanical arrangements for in-flight adjustment of the base configuration for adjusting control surfaces or rotors
B64U 10/20 - Vertical take-off and landing [VTOL] aircraft
Examples relate to uncrewed aerial vehicles (UAVs) and methods for controlled descent during control tier failures. A computing device may initially detect a control tier failure at an UAV. In some examples, the UAV includes a fuselage, a pair of wings extending outwardly from the fuselage, and a pair of stabilizers arranged in a V-shape configuration. Each stabilizer has a control surface that is adjustable relative to a fixed portion of the stabilizer. Based on detecting the control tier failure at the UAV, the computing device may adjust the control surface of each stabilizer from a first angle to a second angle relative to the fixed portion of the stabilizer. By adjusting the angle between the control surfaces and fixed portions of one or both stabilizers, the UAV may induce a deep stall maneuver that can enable a controlled descent of the UAV.
B64U 40/20 - On-board mechanical arrangements for adjusting control surfaces or rotorsOn-board mechanical arrangements for in-flight adjustment of the base configuration for in-flight adjustment of the base configuration
B64U 10/20 - Vertical take-off and landing [VTOL] aircraft
B64U 70/40 - Landing characterised by flight manoeuvres, e.g. deep stall
B64U 101/64 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval
G05D 1/495 - Control of attitude, i.e. control of roll, pitch or yaw to ensure stability
A joiner includes a first and second portions configured to mount to respective first and second structural members. Each of the first and second portions includes a body with a receiving surface to receive the respective structural member. The first portion includes a group of first coupling structures disposed on the first body and the second portion includes a group of second coupling structures disposed on the second body. The first coupling structures are configured to mate with the second coupling structures such that engagement surfaces of the first coupling structures engage engagement surfaces of the second coupling structures so as to transfer loads between the second portion and first portion and to limit relative movement between the first portion and second portion with respect to the first direction and with respect to a vertical direction.
B64U 101/64 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval
A method includes navigating, by a UAV, to a delivery location in an environment; capturing, by at least one sensor on the UAV, sensor data representative of the delivery location; determining, based on the sensor data, a segmented point cloud of the delivery location, wherein the segmented point cloud defines a plurality of point cloud areas with corresponding semantic classifications; determining, based on the segmented point cloud, that a pre-selected delivery point at the delivery location satisfies a condition indicating that a descent path through a cylinder, the cylinder being centered above the pre-selected delivery point and having a radius of a particular lateral distance, does not intersect with any point cloud areas having semantic classifications indicative of an obstacle at the delivery location; and based on determining that the pre-selected delivery point satisfies the condition, initiating, by the UAV, a payload delivery operation towards the pre-selected delivery point.
B64U 101/64 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval
G05D 1/247 - Arrangements for determining position or orientation using signals provided by artificial sources external to the vehicle, e.g. navigation beacons
An unmanned aerial vehicle fleet management system initiates creation of a digital airspace area of operation, presents in a user interface an area classifier selection field configured to select from a set of available area classifiers; receives first user input classifying the digital airspace area of operation as an oversight area; presents a ruleset selection field; receives second user input specifying one or more rulesets of the oversight area; creates the oversight area based at least in part on the first and second inputs; and creates a pilot area associated with the oversight area that inherits the specified ruleset(s) of the oversight area. The oversight area and pilot area define areas of operation of different types for different classes of users, such as pilots and flight operations managers. The specified ruleset(s) comprise rules related to flight approvals. Flight missions can be created or altered based on the specified ruleset(s).
A method includes causing an uncrewed aerial vehicle (UAV) to navigate through a trajectory. The method also includes receiving first motor data representing operation of a first motor during navigation through the trajectory and receiving second motor data representing operation of a second motor during navigation through the trajectory. The method further includes comparing the first motor data with the second motor data. The method also includes, based on the comparison of the first motor data and the second motor data, determining a motor failure state. The method additionally includes causing the UAV to navigate based on the motor failure state.
In some embodiments, a system for efficient coordination of unmanned aerial vehicle (UAV) operations by a first UAV service supplier (USS) in a geographic area within which the first USS and one or more third-party USSes operate UAVs is provided. The system comprises an interoperability computing system configured to perform actions comprising: receiving, by the interoperability computing system, a new operational intent from a rule engine of the first USS; retrieving, by the interoperability computing system, a set of relevant operational intents that are relevant to the new operational intent from a geographic information data store of the first USS; comparing, by the interoperability computing system, the new operational intent to each relevant operational intent of the set of relevant operational intents to detect conflicts; and in response to detecting no conflicts, transmitting, by the interoperability computing system, an approval request to a discovery and synchronization service (DSS).
In some embodiments, a computer-implemented method of efficiently and accurately monitoring aggregate conformance with operational intents for a fleet of unmanned aerial vehicles (UAVs) is provided. A computing system receives telemetry data and operational intents for a plurality of flights during a monitoring period. For each flight of the plurality of flights, the computing system compares the telemetry data associated with the flight to the operational intent associated with the flight; labels each data point of the telemetry data as conformant or non-conformant based on the comparing; and generates a set of excursions based on the labeled data points. The computing system determines a level of aggregate conformance based on the set of excursions, and performs one or more actions in response to the level of aggregate conformance.
In some embodiments, a system for efficient coordination of unmanned aerial vehicle (UAV) operations by a first UAV service supplier (USS) in a geographic area within which the first USS and one or more third-party USSes operate UAVs is provided. The system comprises an interoperability computing system configured to perform actions comprising: receiving, by the interoperability computing system, a new operational intent from a rule engine of the first USS; retrieving, by the interoperability computing system, a set of relevant operational intents that are relevant to the new operational intent from a geographic information data store of the first USS; comparing, by the interoperability computing system, the new operational intent to each relevant operational intent of the set of relevant operational intents to detect conflicts; and in response to detecting no conflicts, transmitting, by the interoperability computing system, an approval request to a discovery and synchronization service (DSS).
In some embodiments, a computer-implemented method of efficiently and accurately monitoring aggregate conformance with operational intents for a fleet of unmanned aerial vehicles (UAVs) is provided. A computing system receives telemetry data and operational intents for a plurality of flights during a monitoring period. For each flight of the plurality of flights, the computing system compares the telemetry data associated with the flight to the operational intent associated with the flight; labels each data point of the telemetry data as conformant or non-conformant based on the comparing; and generates a set of excursions based on the labeled data points. The computing system determines a level of aggregate conformance based on the set of excursions, and performs one or more actions in response to the level of aggregate conformance.
In an example embodiment, a method carried out by an uncrewed aerial vehicle (UAV) may involve receiving a reference map of a cluster of charging pads from a server. The cluster may include a layout of charging pads and fiducial markers distributed across the layout, the reference map representing the layout and fiducial markers. The UAV may fly to the cluster and acquire an image of charging pads and observed fiducial markers near the charging pads. The image may capture an observed constellation of fiducial markers at apparent positions and orientations relative to the charging pads. A reference constellation of fiducial markers at reference positions and orientations relative to reference charging pads may be identified in the reference map. Identities of the reference charging pads and a match of the reference constellation to the observed constellation may be used to disambiguate a particular charging pad from among the charging pads.
In some embodiments, a computer-implemented method for managing resources of a fleet of unmanned aerial vehicles (UAVs) is provided. A computing system creates a mission record and one or more candidate records. Each candidate record of the one or more candidate records represents one or more resources for accomplishing a mission represented by the mission record. The computing system adds a mission node representing the mission record to a resource competition network graph (RCN graph). The computing system adds one or more candidate nodes representing the one or more candidate records to the RCN graph. The computing system determines an optimized allocation of candidate records to mission records using at least a subgraph of the RCN graph. A candidate record is determined to commit to a mission record, and the computing system updates the RCN graph to commit the candidate record to the mission record.
In some embodiments, a computer-implemented method for managing resources of a fleet of unmanned aerial vehicles (UAVs) is provided. A computing system creates a mission record and one or more candidate records. Each candidate record of the one or more candidate records represents one or more resources for accomplishing a mission represented by the mission record. The computing system adds a mission node representing the mission record to a resource competition network graph (RCN graph). The computing system adds one or more candidate nodes representing the one or more candidate records to the RCN graph. The computing system determines an optimized allocation of candidate records to mission records using at least a subgraph of the RCN graph. A candidate record is determined to commit to a mission record, and the computing system updates the RCN graph to commit the candidate record to the mission record.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
G08G 5/32 - Flight plan management for flight plan preparation
62.
COLLABORATIVE INFERENCE BETWEEN CLOUD AND ONBOARD NEURAL NETWORKS FOR UAV DELIVERY APPLICATIONS
A method of collaborative analysis of a ground area by UAV delivery service includes acquiring first and second aerial images of the ground area. The first and second aerial images include depictions of objects at the ground area. A query including an encoding of the first aerial image is transmitted to a cloud-based neural network trained to identify objects. A motion of the UAV is tracked between acquiring the first and second aerial images. A response is received from the cloud-based neural network identifying one or more of the objects depicted in the first aerial image. An onboard neural network disposed on board the UAV is used to identify the objects at the ground area. The onboard neural network receives the response, an indication of the motion tracked between the first and second aerial images, and the second aerial image as input when identifying the objects.
A cleaning structure for a payload retrieval apparatus includes a main body having an upper end and a lower end. The upper end includes a tether attachment point. The cleaning structure also includes a first cleaning component extending outward from the main body. The first cleaning component has a flexible construction for fitting into crevices in the payload retrieval apparatus and defines a cleaning zone around the main body.
A payload retrieval apparatus having a base, an autoloader assembly mounted to the base including: a payload holder configured to hold a payload for retrieval by a UAV, a channel coupled to the payload holder configured to direct a payload retriever suspended from the UAV to the payload holder, and a locking feature configured to lock access to the payload on the payload holder that includes has a movable end that extends through a wall of the channel into an interior of the channel, wherein when the payload retriever contacts the movable end of the locking member, the movable end moves outwardly thereby unlocking the payload on the payload holder, wherein the payload holder is positioned such that when the payload retriever exits the channel, the payload retriever engages a handle of the payload and removes the payload from the payload holder.
B64U 101/66 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval for retrieving parcels
65.
CONVEYOR SYSTEM FOR PAYLOAD RETRIEVAL SYSTEM AND METHOD OF USE
A payload retrieval system includes a support structure and a retriever guide coupled to the support structure. The retriever guide forms a channel having an inlet end and an exit end. The retriever guide is adapted to receive a payload retriever at the inlet end of the channel and direct the payload retriever to the exit end of the channel. The payload retrieval system also includes a holding frame having a payload holder configured to hold a payload for retrieval by the payload retriever when the holding frame is held in an operating position at the exit end of the channel. The system also includes a conveyance system configured to transport the holding frame from a waiting position to the operating position.
B64F 1/32 - Ground or aircraft-carrier-deck installations for handling freight
B65G 35/00 - Mechanical conveyors not otherwise provided for
B64D 1/22 - Taking-up articles from earth's surface
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
66.
COLLABORATIVE INFERENCE BETWEEN CLOUD AND ONBOARD NEURAL NETWORKS FOR UAV DELIVERY APPLICATIONS
A method of collaborative analysis of a ground area by UAV delivery service includes acquiring first and second aerial images of the ground area. The first and second aerial images include depictions of objects at the ground area. A query including an encoding of the first aerial image is transmitted to a cloud-based neural network trained to identify objects. A motion of the UAV is tracked between acquiring the first and second aerial images. A response is received from the cloud-based neural network identifying one or more of the objects depicted in the first aerial image. An onboard neural network disposed on board the UAV is used to identify the objects at the ground area. The onboard neural network receives the response, an indication of the motion tracked between the first and second aerial images, and the second aerial image as input when identifying the objects.
G06V 20/17 - Terrestrial scenes taken from planes or by drones
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
67.
Conveyor System for Payload Retrieval System and Method of Use
A payload retrieval system includes a support structure and a retriever guide coupled to the support structure. The retriever guide forms a channel having an inlet end and an exit end. The retriever guide is adapted to receive a payload retriever at the inlet end of the channel and direct the payload retriever to the exit end of the channel. The payload retrieval system also includes a holding frame having a payload holder configured to hold a payload for retrieval by the payload retriever when the holding frame is held in an operating position at the exit end of the channel. The system also includes a conveyance system configured to transport the holding frame from a waiting position to the operating position.
A cleaning structure for a payload retrieval apparatus includes a main body having an upper end and a lower end. The upper end includes a tether attachment point. The cleaning structure also includes a first cleaning component extending outward from the main body. The first cleaning component has a flexible construction for fitting into crevices in the payload retrieval apparatus and defines a cleaning zone around the main body.
B08B 1/14 - WipesAbsorbent members, e.g. swabs or sponges
F16N 7/12 - Arrangements for supplying oil or unspecified lubricant from a stationary reservoir or the equivalent in or on the machine or member to be lubricated with feed by capillary action, e.g. by wicks
69.
Impact-attenuating tip for a structural member of an aircraft
An uncrewed aerial vehicle (UAV) includes a support extending along a flight direction of the UAV. The support includes an elongate structural member, a cap coupled to a front end of the elongate structural member, and an energy absorber. The support extends along an axis that runs through the support from a front end to a rear end. The cap is coupled to the front end of the elongate structural member. The cap includes a support platform that has a front surface opposite the elongate structural member and that extends outward from the axis. The energy absorber is disposed on the front surface of the support platform and includes a crushable material configured to absorb energy under impact. The UAV also includes a first propeller unit coupled to the support.
A method includes receiving an input specifying a starting location and a destination location for an aerial vehicle. The method additionally includes determining, based on the starting location and the destination location, an aerial path for the aerial vehicle to follow from the starting location to the destination location. The method also includes determining, based on the aerial path, a property of aerial image data, where the aerial image data is obtainable using the aerial vehicle while traversing the aerial path, and where the aerial image data represents an environment along the aerial path. The method further includes determining, based on the property, a path score associated with the aerial path, and outputting the aerial path based on the path score.
A method includes charging a battery of a vehicle to a charge threshold voltage. The method also includes discharging the battery from the charge threshold voltage to a post-task voltage by performing a travel task using the vehicle. The method additionally includes determining that a battery calibration condition has been met. The method further includes, based on determining that the battery calibration condition has been met, discharging the battery from the post-task voltage to a discharge threshold voltage by performing a battery discharge task. The method yet further includes determining a capacity of the battery based on a first electrical output of the battery during the travel task and a second electrical output of the battery during the battery discharge task.
A computer-implemented method includes obtaining an aerial image representing an object in an environment and providing the aerial image as input to a machine learning model. Based on the aerial image, and using the machine learning model, a textual description of a location of the object in the environment is generated and the textual description of the location of the object is outputted.
G06V 20/17 - Terrestrial scenes taken from planes or by drones
G06T 5/50 - Image enhancement or restoration using two or more images, e.g. averaging or subtraction
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
A technique for a UAV includes acquiring a query aerial image with an onboard camera of the UAV and a reference aerial image, the query aerial image including multiple instances of an asset and the reference aerial image including annotated pixels indicating an expected location and an identification for the multiple instances of the asset. The technique further includes identifying a plurality of corresponding pixels between the query aerial image and the reference aerial image, determining a homography transformation describing a relationship between the query aerial image and the reference aerial image, annotating the query aerial image to identify a first instance of the asset included in the multiple instances of the asset within the query aerial image, and instructing the UAV to perform an action associated with the first instance of the asset.
G01S 19/48 - Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
G01S 19/26 - Acquisition or tracking of signals transmitted by the system involving a sensor measurement for aiding acquisition or tracking
G01S 19/40 - Correcting position, velocity or attitude
G05D 1/656 - Interaction with payloads or external entities
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/72 - Data preparation, e.g. statistical preprocessing of image or video features
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
G06V 10/778 - Active pattern-learning, e.g. online learning of image or video features
G06V 10/94 - Hardware or software architectures specially adapted for image or video understanding
G06V 20/17 - Terrestrial scenes taken from planes or by drones
G06V 20/70 - Labelling scene content, e.g. deriving syntactic or semantic representations
B64F 1/35 - Ground or aircraft-carrier-deck installations for supplying electrical power to stationary aircraft
B64U 70/90 - Launching from or landing on platforms
B64U 101/31 - UAVs specially adapted for particular uses or applications for imaging, photography or videography for surveillance
Example embodiments may include determining test flight data based on actual flight data that has been captured by a sensor of an aerial vehicle during a previous flight performed by the aerial vehicle in a physical environment. The test flight data may be processed using a software component that forms part of an aerial vehicle control system. An observed performance of the software component may be determined based on processing the test flight data using the software component. A performance metric may be determined for the software component based on comparing (i) the observed performance of the software component to (ii) an expected performance of the software component. The performance metric may be output.
A technique for a UAV includes acquiring a query aerial image with an onboard camera of the UAV and a reference aerial image, the query aerial image including multiple instances of an asset and the reference aerial image including annotated pixels indicating an expected location and an identification for the multiple instances of the asset. The technique further includes identifying a plurality of corresponding pixels between the query aerial image and the reference aerial image, determining a homography transformation describing a relationship between the query aerial image and the reference aerial image, annotating the query aerial image to identify a first instance of the asset included in the multiple instances of the asset within the query aerial image, and instructing the UAV to perform an action associated with the first instance of the asset.
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06T 3/14 - Transformations for image registration, e.g. adjusting or mapping for alignment of images
G06T 7/30 - Determination of transform parameters for the alignment of images, i.e. image registration
76.
GENERATING AERIAL PATHS BASED ON PROPERTIES OF AERIAL IMAGE DATA
A method includes receiving an input specifying a starting location and a destination location for an aerial vehicle. The method additionally includes determining, based, on the starting location and the destination location, an aerial path for the aerial vehicle to follow from the starting location to the destination location. The method also includes determining, based on the aerial path, a property of aerial image data, where the aerial image data is obtainable using the aerial vehicle while traversing the aerial path, and where the aerial image data, represents an environment along the aerial path. The method further includes determining, based on the property, a path score associated with the aerial path, and outputting the aerial path based on the path score.
G01C 21/00 - NavigationNavigational instruments not provided for in groups
G01C 23/00 - Combined instruments indicating more than one navigational value, e.g. for aircraftCombined measuring devices for measuring two or more variables of movement, e.g. distance, speed or acceleration
G05D 1/46 - Control of position or course in three dimensions
A technique for maintaining a backend terrain model used by a fleet of unmanned aerial vehicles (UAVs) of a UAV service supplier (USS) includes acquiring sensor data of a terrain below a first UAV of the fleet of UAVs as the first UAV executes a mission. The sensor data is analyzed with a terrain detection module disposed on-board the first UAV to determine whether the terrain deviates from a local terrain model describing the terrain. The local terrain model is stored on-board the first UAV. A terrain deviation message is issued from the first UAV to a backend management system of the USS that maintains the backend terrain model in response to a determination that the terrain deviates from the local terrain model. The terrain deviation message includes an indication that a deviant terrain has been identified and location data indicating an approximate location of the deviant terrain.
A technique for maintaining a backend terrain model used by a fleet of unmanned aerial vehicles (UAVs) of a UAV service supplier (USS) includes acquiring sensor data of a terrain below a first UAV of the fleet of UAVs as the first UAV executes a mission. The sensor data is analyzed with a terrain detection module disposed on-board the first UAV to determine whether the terrain deviates from a local terrain model describing the terrain. The local terrain model is stored on-board the first UAV. A terrain deviation message is issued from the first UAV to a backend management system of the USS that maintains the backend terrain model in response to a determination that the terrain deviates from the local terrain model. The terrain deviation message includes an indication that a deviant terrain has been identified and location data indicating an approximate location of the deviant terrain.
G06F 30/13 - Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
79.
USER INTERFACE FOR CREATION OF FLIGHT RESTRICTIONS ON UAV OPERATIONS BASED ON NON-DIGITAL DATA INPUTS
A technique for managing an airspace used by a fleet of UAVs includes presenting a user interface (UI) adapted for creating an airspace restriction based on non-digitized information available to a human supervisor and input into the UI by the human supervisor, soliciting with a selectable field of the UI a restriction type for the airspace restriction from a plurality of available restriction types, soliciting with duration fields of the UI start and end times for the airspace restriction, soliciting with location fields of the UI a location of the airspace restriction, creating a new entry for the airspace restriction in a restriction data store based on the selectable, duration, and location fields, and creating a new flight mission or altering an existing flight mission based upon the airspace restriction.
A technique of camera exposure control for vision-based navigation of an unmanned aerial vehicle (UAV) includes acquiring an aerial image of a ground area below the UAV with an onboard camera system of the UAV, estimating a visual motion factor based on a speed of the UAV and an altitude of the UAV, and adjusting an exposure control setting of the onboard camera system based on the visual motion factor.
G01S 19/47 - Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
G05D 1/611 - Station keeping, e.g. for hovering or dynamic anchoring
A tool for loading a payload on a payload retrieval apparatus includes a support body and a guide extending outward from the support body. The guide has an elongated configuration and a cross-sectional area that is narrower than the support body. The guide is configured to be inserted into a channel of the pay load retrieval apparatus and to position the support body at an end of the channel adjacent to a payload holding structure. The tool also includes a hanger configured to hold the payload. The hanger is movable with respect to the support body between a closed position and a release position.
B64F 1/32 - Ground or aircraft-carrier-deck installations for handling freight
B64D 1/22 - Taking-up articles from earth's surface
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
82.
PAYLOAD HOLDING FACEPLATE FOR PAYLOAD RETRIEVAL SYSTEM
A payload retrieval system includes a support structure and a retriever guide coupled to the support structure. The retriever guide forms a channel having an inlet end and an exit end. The retriever guide is adapted to receive a payload retriever at the inlet end of the channel and direct the payload retriever to the exit end of the channel. The payload retrieval system also includes a faceplate coupled to the retriever guide. The faceplate includes a body extending around a passage aligned with the exit end of the channel, and a payload holder including first and second hooks adapted to hold a payload for receipt by a payload retriever that passes through the retriever guide.
B64F 1/32 - Ground or aircraft-carrier-deck installations for handling freight
B64D 1/22 - Taking-up articles from earth's surface
B64U 101/64 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
A payload retrieval system includes a support structure and a retriever guide coupled to the support structure. The retriever guide includes a group of modular components that form a channel having an inlet end and an exit end. The retriever guide is adapted to receive a payload retriever at the inlet end of the channel and direct the payload retriever to the exit end of the channel. The modular components include a funnel that forms the inlet end of the channel, a rotator downstream of the funnel that is configured to rotate the payload retriever about a direction of travel through the rotator, and an angle adjuster downstream of the rotator that reduces the angle of inclination of the channel. The system also includes a payload holder disposed at the exit end of the channel.
B64D 1/22 - Taking-up articles from earth's surface
B64F 1/32 - Ground or aircraft-carrier-deck installations for handling freight
B64U 101/66 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval for retrieving parcels
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
84.
PAYLOAD RETRIEVAL SYSTEM WITH TETHER RETAINING WALLS
A payload retrieval system includes a support structure and a retriever guide coupled to the support structure. The retriever guide includes a body that forms a channel having an inlet end and an exit end and a tether slot that provides access to the channel. The retriever guide is adapted to receive, at the inlet end of the channel, a payload retriever secured to a tether and to direct the payload retriever to the exit end of the channel while the tether pulls the payload retriever through the retriever guide. The retriever guide also includes a first retaining wall extending upward from the body of the retriever guide along a first side of the tether slot and a second retaining wall extending upward from the body of the retriever guide along a second side of the tether slot. The payload retrieval system also includes a payload holder disposed at the exit end of the channel.
B64D 1/22 - Taking-up articles from earth's surface
B64F 1/32 - Ground or aircraft-carrier-deck installations for handling freight
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
85.
ADAPTIVE CAMERA EXPOSURE CONTROL FOR NAVIGATING A UAV IN LOW LIGHT CONDITIONS
A technique of camera exposure control for vision-based navigation of an unmanned aerial vehicle (UAV) includes acquiring an aerial image of a ground area below the UAV with an onboard camera system of the UAV, estimating a visual motion factor based on a speed of the UAV and an altitude of the UAV, and adjusting an exposure control setting of the onboard camera system based on the visual motion factor.
A package adapted for use with an uncrewed aerial vehicle (UAV) is provided. The package forms a container and has a handle at the top. Embodiments of the package include features for efficient manufacturing and storage.
B65D 25/22 - External fittings for facilitating lifting or suspending of containers
B65D 88/14 - Large containers rigid specially adapted for transport by air
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
A computer-implemented method includes obtaining an aerial image representing an object in an environment and providing the aerial image as input to a machine learning model. Based on the aerial image, and using the machine learning model, a textual description of a location of the object in the environment is generated and the textual description of the location of the object is outputted.
G06V 20/17 - Terrestrial scenes taken from planes or by drones
G06T 5/50 - Image enhancement or restoration using two or more images, e.g. averaging or subtraction
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
An apparatus for landing and launching unmanned aerial vehicles (UAVs) includes a landing pad adapted for receiving the UAVs, a track extending from the landing pad and positioned to engage with the UAVs after the UAVs land on the landing pad, and a charging system positioned to charge the UAVs engaged with the track. The track is adapted to guide or carry the UAVs along the track from the landing pad.
B64U 70/90 - Launching from or landing on platforms
B64U 70/95 - Means for guiding the landing UAV towards the platform, e.g. lighting means
B64U 80/10 - Transport or storage specially adapted for UAVs with means for moving the UAV to a supply or launch location, e.g. robotic arms or carousels
B64U 80/25 - Transport or storage specially adapted for UAVs with arrangements for servicing the UAV for recharging batteriesTransport or storage specially adapted for UAVs with arrangements for servicing the UAV for refuelling
B64U 80/40 - Transport or storage specially adapted for UAVs for two or more UAVs
B64U 80/70 - Transport or storage specially adapted for UAVs in containers
E04H 6/12 - Garages for many vehicles with mechanical means for shifting or lifting vehicles
G08G 5/55 - Navigation or guidance aids for a single aircraft
G08G 5/57 - Navigation or guidance aids for unmanned aircraft
89.
Efficient raster data range query for planned UAV flight segments
A computer system obtains a raster cell of terrain data from a database, a query shape corresponding to a planned flight segment of a UAV that intersects with the raster cell, and a range of acceptable terrain elevation values for the planned flight segment. The raster cell comprises a minimum terrain elevation value, a maximum terrain elevation value, and links to sub-cells of the raster cell. The computer system determines whether the minimum and maximum terrain elevation values of the raster cell are within the range of acceptable terrain elevation values for the planned flight segment and validates the planned flight segment with respect to the raster cell based at least in part on whether the minimum and maximum terrain elevation values of the raster cell are within the range of acceptable terrain elevation values for the planned flight segment.
A technique for mitigating nuisance to a neighborhood from operations of an UAV delivery service includes: calculating nuisance contributions to the neighborhood for each of a plurality of UAV flights over the neighborhood; aggregating the nuisance contributions for each of the UAV flights into a nuisance heat map stored in a nuisance exposure database; receiving, at a machine learning (ML) model, a flight routing request to fly a new delivery mission over the neighborhood; and generating a new flight path for the new delivery mission with the ML model in response to receiving the flight routing request. The ML model is trained to receive the nuisance heat map and the flight routing request as inputs and output the new flight path that optimizes a total nuisance contribution that the new delivery mission will contribute to the neighborhood.
B64U 10/20 - Vertical take-off and landing [VTOL] aircraft
G06N 3/044 - Recurrent networks, e.g. Hopfield networks
G06N 3/084 - Backpropagation, e.g. using gradient descent
G08G 5/32 - Flight plan management for flight plan preparation
G08G 5/55 - Navigation or guidance aids for a single aircraft
G08G 5/57 - Navigation or guidance aids for unmanned aircraft
B64U 101/64 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval
91.
Machine-Learned Monocular Depth Estimation and Semantic Segmentation for 6-DOF Absolute Localization of a Delivery Drone
A method includes receiving a two-dimensional (2D) image captured by a camera on a unmanned aerial vehicle (UAV) and representative of an environment of the UAV. The method further includes applying a trained machine learning model to the 2D image to produce a semantic image of the environment and a depth image of the environment, where the semantic image comprises one or more semantic labels. The method additionally includes retrieving reference depth data representative of the environment, wherein the reference depth data includes reference semantic labels. The method also includes aligning the depth image of the environment with the reference depth data representative of the environment to determine a location of the UAV in the environment, where the aligning associates the one or more semantic labels from the semantic image with the reference semantic labels from the reference depth data.
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
B64U 50/19 - Propulsion using electrically powered motors
B64U 101/30 - UAVs specially adapted for particular uses or applications for imaging, photography or videography
B64U 101/60 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons
G01S 19/48 - Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
In one aspect an uncrewed aerial vehicle (UAV) is provided. The uncrewed aerial vehicle includes a fuselage and a drag reduction device. The fuselage has a front end, a rear end, a top, and a bottom. The drag reduction device includes a proximal end and a distal end. The proximal end of the drag reduction device is coupled to the bottom of the fuselage. The drag reduction device is rotatable between a rest position and an active position in which the drag reduction device extends downward. A standoff is disposed on a rear side of the drag reduction device and is configured to engage a payload secured under the fuselage and hold the drag reduction device at a distance from the payload when the drag reduction device is in the active position.
B64U 20/70 - Constructional aspects of the UAV body
B64U 10/20 - Vertical take-off and landing [VTOL] aircraft
B64C 7/00 - Structures or fairings not otherwise provided for
B64D 1/22 - Taking-up articles from earth's surface
B64D 1/10 - Stowage arrangements for the devices in aircraft
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
93.
UAV FLIGHT CONTROL OPERATIONS FOR PREDICTED TRAFFIC ENCOUNTER
A method is disclosed. The method includes receiving an indication of presence of an aircraft in a vicinity of an uncrewed aerial vehicle (II AV) which is flying along a flight path. The method also includes decelerating, based on the received indication, the UAV to reduce a ground speed along the flight path. The method additionally includes descending, after reducing the ground, speed, the UAV to a hover position. The method further includes determining, while the UAV is in the hover position, whether to resume the flight path or to land the UAV based on a determination of continued presence of the aircraft in the vicinity of the UAV. The method also includes controlling the UAV based on the determination of whether to resume the flight path or to land the UAV.
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.
B64D 1/22 - Taking-up articles from earth's surface
B64U 101/30 - UAVs specially adapted for particular uses or applications for imaging, photography or videography
B64U 101/64 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons for parcel delivery or retrieval
B64U 101/67 - UAVs specially adapted for particular uses or applications for transporting passengersUAVs specially adapted for particular uses or applications for transporting goods other than weapons the UAVs comprising tethers for lowering the goods
G05D 1/46 - Control of position or course in three dimensions
G05D 1/689 - Pointing payloads towards fixed or moving targets
95.
INTEGRATION OF UAV DELIVERY SERVICES IN THIRD-PARTY SYSTEMS
In some embodiments, a method of managing deliveries of orders by a fleet of unmanned aerial vehicles (UAVs) from retail fulfillment locations to delivery locations is provided. A fleet management computing system receives a request for delivery of an order from a retailer ordering computing system. The fleet management computing system transmits one or more package identifiers to be associated with one or more packages for the order. The fleet management computing system receives a notification that a package of the one or more packages for the order is ready for pickup at a retail fulfillment location. The fleet management computing system determines a navigation route for a UAV to the delivery location via the retail fulfillment location. The fleet management computing system transmits the navigation route to the UAV for autonomous navigation of the navigation route to the delivery location via the retail fulfillment location to deliver the package.
In some embodiments, a method of planning a navigation route for an autonomous vehicle is provided. A computing system receives mission information including a start location and a goal location. The computing system generates a representation of an operation area that includes the start location and the goal location. The computing system updates the representation of the operation area based on one or more temporary obstacles. The computing system provides the representation of the operation area, the start location, and the goal location as input to a machine-learning model to generate a cost-to-go map of the operation area. The computing system determines the navigation route using the cost-to-go map of the operation area.
An apparatus may include a substrate. The apparatus may also include a first charger terminal disposed on the substrate, including silver, and configured, to apply a first electric potential to a first battery terminal of a battery. The apparatus may additionally include a second charger terminal disposed on the substrate, comprising silver, and configured to apply a second electric potential to a second battery terminal of the battery.
In some embodiments, a method of managing deliveries of orders by a fleet of unmanned aerial vehicles (UAVs) from retail fulfillment locations to delivery locations is provided. A fleet management computing system receives a request for delivery of an order from a retailer ordering computing system. The fleet management computing system transmits one or more package identifiers to be associated with one or more packages for the order. The fleet management computing system receives a notification that a package of the one or more packages for the order is ready for pickup at a retail fulfillment location. The fleet management computing system determines a navigation route for a UAV to the delivery location via the retail fulfillment location. The fleet management computing system transmits the navigation route to the UAV for autonomous navigation of the navigation route to the delivery location via the retail fulfillment location to deliver the package.
An apparatus may include a substrate. The apparatus may also include a first charger terminal disposed on the substrate and configured to apply a first electric potential to a first battery terminal of a battery. The apparatus may additionally include a second charger terminal disposed on the substrate and configured to apply a second electric potential to a second battery terminal of the battery. The apparatus may further include a barrier located on the substrate between the first charger terminal and the second charger terminal and configured to electrically isolate the first charger terminal and the second charger terminal by obstructing formation of a conductive path by way of a liquid disposed on the substrate.
In some embodiments, a method of planning a navigation route for an autonomous vehicle is provided. A computing system receives mission information including a start location and a goal location. The computing system generates a representation of an operation area that includes the start location and the goal location. The computing system updates the representation of the operation area based on one or more temporary obstacles. The computing system provides the representation of the operation area, the start location, and the goal location as input to a machine-learning model to generate a cost-to-go map of the operation area. The computing system determines the navigation route using the cost-to-go map of the operation area.
