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 - Scènes terrestres transmises par des avions ou des drones
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
2.
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 - LingettesÉléments absorbants, p. ex. écouvillons ou éponges
F16N 7/12 - Installations à huile ou autre lubrifiant non spécifié, à réservoir ou autre source portés par la machine ou l'organe machine à lubrifier avec alimentation par action capillaire, p. ex. par des mèches
4.
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.
G06V 20/17 - Scènes terrestres transmises par des avions ou des drones
G05D 1/243 - Moyens de capture de signaux provenant naturellement de l’environnement, p. ex. signaux optiques, acoustiques, gravitationnels ou magnétiques ambiants
G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
G06V 10/70 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique
6.
Vehicle Battery Capacity Measurement Using Autonomous Discharge
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.
H02J 7/00 - Circuits pour la charge ou la dépolarisation des batteries ou pour alimenter des charges par des batteries
G01R 31/3835 - Dispositions pour la surveillance de variables des batteries ou des accumulateurs, p. ex. état de charge ne faisant intervenir que des mesures de tension
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 - Scènes terrestres transmises par des avions ou des drones
G06T 5/50 - Amélioration ou restauration d'image utilisant plusieurs images, p. ex. moyenne ou soustraction
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
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 20/17 - Scènes terrestres transmises par des avions ou des drones
B64F 1/35 - Installations au sol ou installations pour ponts d'envol des porte-avions pour l'alimentation en énergie électrique des aéronefs en stationnement
B64U 70/90 - Lancement à partir de ou atterrissage sur des plates-formes
B64U 101/31 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie à la surveillance
G05D 1/656 - Interaction avec des charges utiles ou des entités externes
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/72 - Préparation de données, p. ex. prétraitement statistique des caractéristiques d’images ou de vidéos
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/77 - Traitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source
G06V 10/778 - Apprentissage de profils actif, p. ex. apprentissage en ligne des caractéristiques d’images ou de vidéos
G06V 10/94 - Architectures logicielles ou matérielles spécialement adaptées à la compréhension d’images ou de vidéos
G06V 20/70 - Étiquetage du contenu de scène, p. ex. en tirant des représentations syntaxiques ou sémantiques
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 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
G06T 3/14 - Transformations pour le recalage d’images, p. ex. ajustement ou mappage pour l’alignement d’images
G06T 7/30 - Détermination des paramètres de transformation pour l'alignement des images, c.-à-d. recalage des images
11.
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 - NavigationInstruments de navigation non prévus dans les groupes
G01C 23/00 - Instruments combinés indiquant plus d’une valeur de navigation, p. ex. pour l’aviationDispositifs de mesure combinés pour mesurer plusieurs variables du mouvement, p. ex. la distance, la vitesse ou l’accélération
G05D 1/46 - Commande de la position ou du cap dans les trois dimensions
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
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 - Conception architecturale, p. ex. conception architecturale assistée par ordinateur [CAAO] relative à la conception de bâtiments, de ponts, de paysages, d’usines ou de routes
14.
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.
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 - Installations au sol ou installations pour ponts d'envol des porte-avions pour la manutention du fret
B64D 1/22 - Enlèvement d'objets à la surface du sol
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
17.
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 - Installations au sol ou installations pour ponts d'envol des porte-avions pour la manutention du fret
B64D 1/22 - Enlèvement d'objets à la surface du sol
B64U 101/64 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
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 - Enlèvement d'objets à la surface du sol
B64F 1/32 - Installations au sol ou installations pour ponts d'envol des porte-avions pour la manutention du fret
B64U 101/66 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis au retrait de colis
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
19.
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 - Enlèvement d'objets à la surface du sol
B64F 1/32 - Installations au sol ou installations pour ponts d'envol des porte-avions pour la manutention du fret
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
20.
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 - Accessoires externes pour faciliter le levage ou la suspension des réceptacles
B65D 88/14 - Grands réceptacles rigides spécialement conçus pour le transport par air
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
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 - Scènes terrestres transmises par des avions ou des drones
G06T 5/50 - Amélioration ou restauration d'image utilisant plusieurs images, p. ex. moyenne ou soustraction
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
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.
E04H 6/44 - Bâtiments pour garer des voitures, du matériel roulant, des avions, des bateaux ou d’autres véhicules, p. ex. garages pour garer des avions
B60L 53/30 - Détails de construction des stations de charge
B64U 70/90 - Lancement à partir de ou atterrissage sur des plates-formes
B64U 70/95 - Moyens de guidage du véhicule aérien sans pilote atterrissant vers la plate-forme, p. ex. moyens d’éclairage
B64U 80/10 - Transport ou stockage spécialement adaptés aux véhicules aériens sans pilote avec des moyens de déplacement du véhicule aérien sans pilote vers un emplacement d’alimentation ou de lancement, p. ex. armes robotiques ou carrousels
B64U 80/25 - Transport ou stockage spécialement adaptés aux véhicules aériens sans pilote avec des dispositions pour assurer le service du véhicule aérien sans pilote pour la recharge de batteriesTransport ou stockage spécialement adaptés aux véhicules aériens sans pilote avec des dispositions pour assurer le service du véhicule aérien sans pilote pour le ravitaillement en combustible
B64U 80/40 - Transport ou stockage spécialement adaptés aux véhicules aériens sans pilote à plusieurs véhicules aériens sans pilote
B64U 80/70 - Transport ou stockage spécialement adaptés aux véhicules aériens sans pilote dans des réceptacles
E04H 6/12 - Garages pour de nombreux véhicules avec moyens mécaniques pour déplacer ou élever les véhicules
G08G 5/55 - Aides à la navigation ou au guidage pour un seul aéronef
G08G 5/57 - Aides à la navigation ou au guidage pour les aéronefs sans pilote
24.
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 - Aéronefs à décollage et atterrissage verticaux [ADAV, en anglais VTOL]
G06N 3/044 - Réseaux récurrents, p. ex. réseaux de Hopfield
G06N 3/084 - Rétropropagation, p. ex. suivant l’algorithme du gradient
G08G 5/32 - Gestion des plans de vol pour la préparation des plans de vol
G08G 5/55 - Aides à la navigation ou au guidage pour un seul aéronef
G08G 5/57 - Aides à la navigation ou au guidage pour les aéronefs sans pilote
B64U 101/64 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis
26.
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 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
B64U 50/19 - Propulsion utilisant des moteurs électriques
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
B64U 101/60 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes
G01S 19/48 - Détermination de position en combinant ou en commutant entre les solutions de position dérivées du système de positionnement par satellite à radiophares et les solutions de position dérivées d'un autre système
G06T 7/50 - Récupération de la profondeur ou de la forme
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.
C22B 3/04 - Extraction de composés métalliques par voie humide à partir de minerais ou de concentrés par lixiviation
C22B 3/12 - Extraction de composés métalliques par voie humide à partir de minerais ou de concentrés par lixiviation dans des solutions inorganiques alcalines
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 - Enlèvement d'objets à la surface du sol
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
B64U 101/64 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
G05D 1/46 - Commande de la position ou du cap dans les trois dimensions
G05D 1/689 - Interaction avec des charges utiles ou des entités externes dirigeant des charges utiles vers des cibles fixes ou en mouvement
30.
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.
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.
B60L 53/16 - Connecteurs, p. ex. fiches ou prises, spécialement adaptés pour recharger des véhicules électriques
B64F 1/35 - Installations au sol ou installations pour ponts d'envol des porte-avions pour l'alimentation en énergie électrique des aéronefs en stationnement
A method includes capturing, by a sensor on an unmanned aerial vehicle (UAV), an image of a delivery location. The method also includes determining, based on the image of the delivery location, a segmentation image. The segmentation image segments the delivery location into a plurality of pixel areas with corresponding semantic classifications. The method additionally includes determining, based on the segmentation image, a percentage of obstacle pixels within a surrounding area of a delivery point at the delivery location, wherein each obstacle pixel has a semantic classification indicative of an obstacle in the delivery location. The method further includes based on the percentage of obstacle pixels being above a threshold percentage, aborting a delivery process of the UAV.
G06V 20/17 - Scènes terrestres transmises par des avions ou des drones
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
B64U 101/60 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes
G05D 1/485 - Commande du taux de modification de l’altitude ou de la profondeur
G05D 1/689 - Interaction avec des charges utiles ou des entités externes dirigeant des charges utiles vers des cibles fixes ou en mouvement
G06Q 10/0832 - Marchandises spéciales ou procédures de manutention spéciales, p. ex. manutention de marchandises dangereuses ou fragiles
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
38.
DAY/NIGHT FILTER GLASS FOR AIRCRAFT CAMERA SYSTEMS
A technique for using an onboard camera capable of day and night operation on an unmanned aerial vehicle (UAV) includes: traveling along a route of the UAV at night; and acquiring an aerial image with an onboard camera. The onboard camera includes: a sensor device for receiving photons and converting the photons into photoelectrons; a processor for processing the photoelectrons into an image file; a lens positioned adjacent to the sensor device for focusing the photons on the sensor device; and a filter positioned adjacent an outer surface of the lens. The filter can permit photons in the infrared light spectrum to pass to the lens, and attenuate at least a portion of the photons in the visible light spectrum prior to reaching the lens.
G03B 11/00 - Filtres ou autres intercepteurs spécialement adaptés pour les besoins photographiques
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
G03B 15/00 - Procédés particuliers pour prendre des photographiesAppareillage à cet effet
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
G06V 20/17 - Scènes terrestres transmises par des avions ou des drones
H04N 7/18 - Systèmes de télévision en circuit fermé [CCTV], c.-à-d. systèmes dans lesquels le signal vidéo n'est pas diffusé
H04N 23/11 - Caméras ou modules de caméras comprenant des capteurs d'images électroniquesLeur commande pour générer des signaux d'image à partir de différentes longueurs d'onde pour générer des signaux d'image à partir de longueurs d'onde de lumière visible et infrarouge
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.
B64U 101/66 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis au retrait de colis
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
40.
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.
B64U 101/64 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
41.
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 - Enlèvement d'objets à la surface du sol
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
42.
PAYLOAD RETRIEVAL APPARATUS WITH INTERNAL UNLOCKING FEATURE AND SECURITY FEATURES FOR USE WITH A UAV
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 pay load 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 pay load on the payload holder, wherein the payload holder is positioned such that when the payload retriever exits the channel, the pay load retriever engages a handle of the pay load and removes the payload from the payload holder.
B64F 1/32 - Installations au sol ou installations pour ponts d'envol des porte-avions pour la manutention du fret
B64D 1/22 - Enlèvement d'objets à la surface du sol
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
43.
DAY/NIGHT FILTER GLASS FOR AIRCRAFT CAMERA SYSTEMS
A technique for using an onboard camara capable of day and night operation on an unmanned aerial vehicle (UAV) includes: traveling along a route of the UAV at night; and acquiring an aerial image with an onboard camera. The onboard camera includes: a sensor device for receiving photons and converting the photons into photoelectrons; a processor for processing the photoelectrons into an image file; a lens positioned adjacent to the sensor device for focusing the photons on the sensor device; and a filter positioned adjacent an outer surface of the lens. The filter can permit photons in the infrared light spectrum to pass to the lens, and attenuate at least a portion of the photons in the visible light spectrum prior to reaching the lens.
H04N 23/57 - Détails mécaniques ou électriques de caméras ou de modules de caméras spécialement adaptés pour être intégrés dans d'autres dispositifs
G03B 15/00 - Procédés particuliers pour prendre des photographiesAppareillage à cet effet
B64U 20/87 - Montage des dispositifs d’imagerie, p. ex. montage des suspensions à cardan
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
44.
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.
G05D 1/229 - Données d’entrée de commande, p. ex. points de passage
G06F 3/04883 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique utilisant un écran tactile ou une tablette numérique, p. ex. entrée de commandes par des tracés gestuels pour l’entrée de données par calligraphie, p. ex. sous forme de gestes ou de texte
A method for perception validation of an unmanned aerial vehicle (UAV) includes: acquiring an aerial image of a ground area with an onboard camera system of the UAV, generating a semantic above ground altitude (AGL) estimate with a neural network trained to output the semantic AGL estimate in response to the aerial image fed as an input to the neural network, generating a motion estimate or a position estimate based upon perception sensor data output from a perception sensor disposed onboard the UAV, and cross-validating the motion or position estimate against the semantic AGL estimate.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G01C 5/00 - Mesure des hauteursMesure des distances transversales par rapport à la ligne de viséeNivellement entre des points séparésNiveaux à lunette
G01C 21/16 - NavigationInstruments de navigation non prévus dans les groupes en utilisant des mesures de la vitesse ou de l'accélération exécutées à bord de l'objet navigantNavigation à l'estime en intégrant l'accélération ou la vitesse, c.-à-d. navigation par inertie
09 - Appareils et instruments scientifiques et électriques
12 - Véhicules; appareils de locomotion par terre, par air ou par eau; parties de véhicules
39 - Services de transport, emballage et entreposage; organisation de voyages
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Transportation logistics services, namely, arranging, planning, and scheduling the delivery of goods by drone for others; Business management of logistics for others; Logistics management in the field of drone delivery, retail, delivery, and transportation; Business advisory services in the field of transportation logistics 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 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 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
47.
UAV PERCEPTION VALIDATION BASED UPON A SEMANTIC AGL ESTIMATE
A method for perception validation of an unmanned aerial vehicle (UAV) includes: acquiring an aerial image of a ground area with an onboard camera system of the UAV, generating a semantic above ground altitude (AGL) estimate with a neural network trained to output the semantic AGL estimate in response to the aerial image fed as an input to the neural network, generating a motion estimate or a position estimate based upon perception sensor data output from a perception sensor disposed onboard the UAV, and cross-validating the motion or position estimate against the semantic AGL estimate.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
48.
UAV Route Planning for Mitigating Traffic Encounters
A method is disclosed. The method includes receiving data for one or more aircraft currently flying within an airspace. The received data for each of the one or more aircraft includes a current position and at least one aircraft parameter. Based on the current position and the at least one aircraft parameter, the method also includes determining an initial volume and a predicted future trajectory for each of the one or more aircraft. The method additionally includes determining, based on the predicted future trajectory and the initial volume, an extended volume for each of the one or more aircraft. The method further includes determining, based on the extended volume determined for each of the one or more aircraft, a composite extended volume space. The method includes planning a flight path for an unmanned aerial vehicle (UAV) through the airspace based on the composite extended volume space.
A method is disclosed. The method includes receiving data for one or more aircraft currently flying within an airspace. The received data for each of the one or more aircraft includes a current position and at least one aircraft parameter. Based on the current position and the at least one aircraft parameter, the method also includes determining an initial volume and a predicted future trajectory for each of the one or more aircraft. The method additionally includes determining, based on the predicted future trajectory and the initial volume, an extended volume for each of the one or more aircraft. The method further includes determining, based on the extended volume determined for each of the one or more aircraft, a composite extended volume space. The method includes planning a flight path for an unmanned aerial vehicle (UAV) through the airspace based on the composite extended volume space.
G05D 1/46 - Commande de la position ou du cap dans les trois dimensions
G05D 1/246 - Dispositions pour déterminer la position ou l’orientation utilisant des cartes d’environnement, p. ex. localisation et cartographie simultanées [SLAM]
An uncrewed aerial vehicle (UAV) may be configured to hover above a particular charging pad within a portion of a cluster of charging pads for UAVs. The cluster may include the charging pads arranged in a layout and fiducial markers distributed at positions across the layout. While hovering above the particular charging pad, the UAV may capture an aerial image of the portion of the cluster. The UAV may derive cluster-portion observation data from the image, the cluster-portion observation data including information indicating a position of the particular charging pad, and positions of one or more fiducial markers within the portion of the cluster relative to the particular charging pad. The UAV may send the cluster-portion observation data to a computing system in an infrastructure support network for UAVs, and thereafter receive, from the computing system, location information indicating that UAV's geolocation is a geolocation of the particular charging pad.
G05D 1/611 - Maintien de la position, p. ex. pour un ancrage en vol stationnaire ou dynamique
G05D 1/244 - Dispositions pour déterminer la position ou l’orientation utilisant des aides à la navigation passive extérieures au véhicule, p. ex. marqueurs, réflecteurs ou moyens magnétiques
G06V 20/17 - Scènes terrestres transmises par des avions ou des drones
G05D 1/248 - Dispositions pour déterminer la position ou l’orientation utilisant des signaux fournis par des sources artificielles extérieures au véhicule, p. ex. balises de navigation générés par des satellites, p. ex. GPS
B64U 80/25 - Transport ou stockage spécialement adaptés aux véhicules aériens sans pilote avec des dispositions pour assurer le service du véhicule aérien sans pilote pour la recharge de batteriesTransport ou stockage spécialement adaptés aux véhicules aériens sans pilote avec des dispositions pour assurer le service du véhicule aérien sans pilote pour le ravitaillement en combustible
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 payload 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.
A method of operation of an unmanned aerial vehicle (UAV) service includes acquiring aerial images of a scene at an area of interest (AOI), wherein the aerial images are acquired with a UAV of the UAV service during a flight mission of the UAV that passes over the AOI; uploading a mission log of the flight mission to a backend data system of the UAV service, the mission log including image data that includes, or is derived from, at least a portion of the aerial images; and training a neural radiance field (NeRF) model with one or more of the aerial images, wherein the NeRF model comprises a neural network, which after the training, encodes a volumetric representation of the scene capable of generating novel views of the scene different than any of the aerial images used to train the NeRF model.
G05D 1/243 - Moyens de capture de signaux provenant naturellement de l’environnement, p. ex. signaux optiques, acoustiques, gravitationnels ou magnétiques ambiants
G05D 1/246 - Dispositions pour déterminer la position ou l’orientation utilisant des cartes d’environnement, p. ex. localisation et cartographie simultanées [SLAM]
G05D 1/667 - Livraison ou récupération de charges utiles
A method of operation of an unmanned aerial vehicle (UAV) service includes acquiring aerial images of a scene at an area of interest (AOI), wherein the aerial images are acquired with a UAV of the UAV service during a flight mission of the UAV that passes over the AOI; uploading a mission log of the flight mission to a backend data system of the UAV service, the mission log including image data that includes, or is derived from, at least a portion of the aerial images; and training a neural radiance field (NeRF) model with one or more of the aerial images, wherein the NeRF model comprises a neural network, which after the training, encodes a volumetric representation of the scene capable of generating novel views of the scene different than any of the aerial images used to train the NeRF model.
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.
B64U 101/66 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis au retrait de colis
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
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.
B64C 23/00 - Moyens permettant d'influencer l'écoulement d'air sur les surfaces des aéronefs, non prévus ailleurs
B64D 1/10 - Arrimage de ces dispositifs sur aéronefs
B64U 101/60 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes
56.
STATISTICAL ESTIMATION OF LOCAL MINIMUM FLYABLE AGLS BASED ON PROBABILITIES OF PLANNED FLIGHTS INTERSECTING TERRAIN ESTIMATES
A method comprises determining an occupancy grid of an area for unmanned aerial vehicle (UAV) navigation. The method further comprises determining, based on the occupancy grid, a candidate flyable airspace through which to permit UAV navigation and determining, by a UAV route planner, a plurality of UAV flight paths through the candidate flyable airspace. The method further comprises determining, based on the occupancy grid, a probability value of the plurality of UAV flight paths intersecting an occupied volume. The method additionally comprises determining whether the probability value of the plurality of UAV flight paths intersecting the occupied volume is below a threshold value and, based on determining that the probability value of the plurality of UAV flight paths intersecting the occupied volume is below the threshold value, validating the candidate flyable airspace for the UAV route planner to plan a route for a UAV to navigate through the area.
G05D 1/246 - Dispositions pour déterminer la position ou l’orientation utilisant des cartes d’environnement, p. ex. localisation et cartographie simultanées [SLAM]
G05D 1/46 - Commande de la position ou du cap dans les trois dimensions
G05D 1/644 - Optimisation des paramètres de parcours, p. ex. consommation d’énergie, réduction du temps de parcours ou de la distance
A technique performed by UAV delivery system includes: arriving by a UAV of over a destination area; capturing a plurality of aerial images of a scene at the destination area with an onboard camera system of the UAV while flying above the destination area, wherein the aerial images capture the scene from a plurality of UAV vantage points offset from each other; optimizing weights of a generative neural network (GNN) using at least some of the aerial images as a training dataset to encode a volumetric representation of the scene into the GNN, wherein the weights are optimized by an onboard processing system of the UAV; and communicating the GNN with the weights optimized to a backend datacenter in communication with the UAV to transmit the volumetric representation of the scene over which the UAV flew without transmitting the aerial images themselves to the backend datacenter.
G06V 20/17 - Scènes terrestres transmises par des avions ou des drones
G06V 20/56 - Contexte ou environnement de l’image à l’extérieur d’un véhicule à partir de capteurs embarqués
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06T 7/593 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir d’images stéréo
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06T 7/579 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir du mouvement
A method comprises determining an occupancy grid of an area for unmanned aerial vehicle (UAV) navigation. The method further comprises determining, based on the occupancy grid, a candidate flyable airspace through which to permit UAV navigation and determining, by a UAV route planner, a plurality of UAV flight paths through the candidate flyable airspace. The method further comprises determining, based on the occupancy grid, a probability value of the plurality of UAV flight paths intersecting an occupied volume. The method additionally comprises determining whether the probability value of the plurality of UAV flight paths intersecting the occupied volume is below a threshold value and, based on determining that the probability value of the plurality of UAV flight paths intersecting the occupied volume is below the threshold value, validating the candidate flyable airspace for the UAV route planner to plan a route for a UAV to navigate through the area.
A method includes causing an aerial vehicle to deploy a tethered component to a particular distance beneath the aerial vehicle by releasing a tether connecting the tethered component to the aerial vehicle. The method also includes obtaining, from a camera connected to the aerial vehicle, image data that represents the tethered component while the tethered component is deployed to the particular distance beneath the aerial vehicle. The method additionally includes determining, based on the image data, a position of the tethered component within the image data. The method further includes determining, based on the position of the tethered component within the image data, a wind vector that represents a wind condition present in an environment of the aerial vehicle. The method yet further includes causing the aerial vehicle to perform an operation based on the wind vector.
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
B64D 47/02 - Aménagements ou adaptations des dispositifs de signalisation ou d'éclairage
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
G06F 18/2413 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques basées sur les distances des motifs d'entraînement ou de référence
G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
60.
COMPRESSING A SCENE INTO A GENERATIVE NEURAL NETWORK FOR UAV SCENE ANALYSIS APPLICATIONS
A technique performed by UAV delivery system includes: arriving by a UAV of over a destination area; capturing a plurality of aerial images of a scene at the destination area with an onboard camera system of the UAV while flying above the destination area, wherein the aerial images capture the scene from a plurality of UAV vantage points offset from each other; optimizing weights of a generative neural network (GNN) using at least some of the aerial images as a training dataset to encode a volumetric representation of the scene into the GNN, wherein the weights are optimized by an onboard processing system of the UAV; and communicating the GNN with the weights optimized to a backend datacenter in communication with the UAV to transmit the volumetric representation of the scene over which the UAV flew without transmitting the aerial images themselves to the backend datacenter.
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
B64U 10/20 - Aéronefs à décollage et atterrissage verticaux [ADAV, en anglais VTOL]
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
B64U 101/60 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes
G06T 7/579 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir du mouvement
G06T 7/593 - Récupération de la profondeur ou de la forme à partir de plusieurs images à partir d’images stéréo
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 20/17 - Scènes terrestres transmises par des avions ou des drones
61.
CORRECTING ERRONEOUS UAV POSITIONING INFORMATION USING SEMANTICALLY SEGMENTED IMAGES
In some embodiments, a method for autonomous navigation of an unmanned aerial vehicle (UAV) is provided. The UAV determines a tracked position using at least one positioning sensor of the UAV. The UAV captures an image using a camera of the UAV. The UAV determines a visual position confidence area using the captured image. The UAV checks the tracked position using the visual position confidence area to determine whether the tracked position is accurate. In response to determining that the tracked position is not accurate, the UAV causes a corrective action based on the visual position confidence area to be taken.
A technique for a UAV includes: acquiring an aerial image of an area below a UAV that includes one or more instances of an object; analyzing the aerial image with an image classifier to classify select pixels of the aerial image as being keypoint pixels associated with keypoints of the object; grouping the keypoint pixels into one or more groups each associated with one of the instances of the object, wherein first keypoint pixels of the keypoint pixels are grouped into a first group of the one or more groups associated with a first instance of the one or more instances of the object; generating an estimate of a relative position of the UAV to the first instance of the object based at least upon a machine vision analysis of the first keypoint pixels; and navigating the UAV into alignment with the first instance based upon the estimate.
A technique for a UAV includes: acquiring an aerial image of an area below a UAV that includes one or more instances of an object; analyzing the aerial image with an image classifier to classify select pixels of the aerial image as being keypoint pixels associated with keypoints of the object; grouping the keypoint pixels into one or more groups each associated with one of the instances of the object, wherein first keypoint pixels of the keypoint pixels are grouped into a first group of the one or more groups associated with a first instance of the one or more instances of the object; generating an estimate of a relative position of the UAV to the first instance of the object based at least upon a machine vision analysis of the first keypoint pixels; and navigating the UAV into alignment with the first instance based upon the estimate.
G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
B64D 45/00 - Indicateurs ou dispositifs de protection d'aéronefs, non prévus ailleurs
B64U 10/20 - Aéronefs à décollage et atterrissage verticaux [ADAV, en anglais VTOL]
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
B64U 101/66 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis au retrait de colis
G06V 20/17 - Scènes terrestres transmises par des avions ou des drones
64.
CORRECTING ERRONEOUS UAV POSITIONING INFORMATION USING SEMANTICALLY SEGMENTED IMAGES
In some embodiments, a method for autonomous navigation of an unmanned aerial vehicle (UAV) is provided. The UAV determines a tracked position using at least one positioning sensor of the UAV. The UAV captures an image using a camera of the UAV. The UAV determines a visual position confidence area using the captured image. The UAV checks the tracked position using the visual position confidence area to determine whether the tracked position is accurate. In response to determining that the tracked position is not accurate, the UAV causes a corrective action based on the visual position confidence area to be taken.
B64U 10/20 - Aéronefs à décollage et atterrissage verticaux [ADAV, en anglais VTOL]
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 20/17 - Scènes terrestres transmises par des avions ou des drones
65.
AUTOMATED DISCOVERY AND MONITORING OF UNCREWED AERIAL VEHICLE GROUND-SUPPORT INFRASTRUCTURE
A computing system in an infrastructure support network for uncrewed aerial vehicles (UAVs) may receive, from a UAV, aerial observation data of a ground-based cluster of charging pads for UAVs, the cluster comprising assets including the charging pads arranged in a layout and fiducial markers distributed across the layout. The aerial observation data may comprise position measurements of the UAV at aerial geolocations above the cluster, and vector positions of one or more assets with respect to the aerial geolocations. The computing system may generate a map graph from the aerial observation data, the map graph comprising (i) nodes corresponding to both the aerial geolocations and vector positions, and (ii) edges between pairs of selected nodes, the edges corresponding to distances between selected nodes and including measurement uncertainties. The computing system may generate a spatial map of cluster assets of the cluster by computationally optimizing the map graph.
An uncrewed aerial vehicle (UAV) may be configured to hover above a particular charging pad within a portion of a cluster of charging pads for UAVs. The cluster may include the charging pads arranged in a layout and fiducial markers distributed at positions across the layout. While hovering above the particular charging pad, the UAV may capture an aerial image of the portion of the cluster. The UAV may derive cluster-portion observation data from the image, the cluster-portion observation data including information indicating a position of the particular charging pad, and positions of one or more fiducial markers within the portion of the cluster relative to the particular charging pad. The UAV may send the cluster-portion observation data to a computing system in an infrastructure support network for UAVs, and thereafter receive, from the computing system, location information indicating that UAV's geolocation is a geolocation of the particular charging pad.
G05D 1/244 - Dispositions pour déterminer la position ou l’orientation utilisant des aides à la navigation passive extérieures au véhicule, p. ex. marqueurs, réflecteurs ou moyens magnétiques
G05D 1/246 - Dispositions pour déterminer la position ou l’orientation utilisant des cartes d’environnement, p. ex. localisation et cartographie simultanées [SLAM]
A computing system in an infrastructure support network for uncrewed aerial vehicles (UAVs) may receive, from a UAV, aerial observation data of a ground-based cluster of charging pads for UAVs, the cluster comprising assets including the charging pads arranged in a layout and fiducial markers distributed across the layout. The aerial observation data may comprise position measurements of the UAV at aerial geolocations above the cluster, and vector positions of one or more assets with respect to the aerial geolocations. The computing system may generate a map graph from the aerial observation data, the map graph comprising (i) nodes corresponding to both the aerial geolocations and vector positions, and (ii) edges between pairs of selected nodes, the edges corresponding to distances between selected nodes and including measurement uncertainties. The computing system may generate a spatial map of cluster assets of the cluster by computationally optimizing the map graph.
A method includes determining an operational condition associated with an unmanned aerial vehicle (UAV). The method includes, responsive to determining the operational condition, causing the UAV to perform a pre-flight check. The pre-flight check includes hovering the UAV above a takeoff location. The pre-flight check includes, while hovering the UAV, moving one or more controllable components of the UAV in accordance with a predetermined sequence of movements. The pre-flight check includes obtaining, by one or more sensors of the UAV, sensor data indicative of a flight response of the UAV to moving the one or more controllable components while hovering the UAV. The pre-flight check includes comparing the sensor data to expected sensor data associated with an expected flight response to the predetermined sequence of movements while hovering the UAV. The pre-flight check includes, based on comparing the sensor data to the expected sensor data, evaluating performance of the UAV.
G08G 5/26 - Transmission d’informations relatives au trafic entre les aéronefs et les stations au sol
B64U 50/13 - Propulsion utilisant des soufflantes ou des hélices externes
B64U 101/60 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
69.
PAYLOAD RETRIEVER HAVING MULTIPLE SLOTS FOR USE WITH A UAV
A pay load 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 pay load.
B64D 1/22 - Enlèvement d'objets à la surface du sol
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
70.
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.
In some embodiments, a non-transitory computer-readable medium having logic stored thereon is provided. The logic, in response to execution by one or more processors of an unmanned aerial vehicle (UAV), causes the UAV to perform actions comprising receiving at least one ADS-B message from an intruder aircraft; generating a intruder location prediction based on the at least one ADS-B message; comparing the intruder location prediction to an ownship location prediction to detect conflicts; and in response to detecting a conflict between the intruder location prediction and the ownship location prediction, determining a safe landing location along a planned route for the UAV and descending to land at the safe landing location.
B64U 10/20 - Aéronefs à décollage et atterrissage verticaux [ADAV, en anglais VTOL]
B64U 101/00 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
A package adapted for use with an uncrewed aerial vehicle (UAV) is provided. The package includes a hanger, an enclosure component and a first structure component. The hanger includes a base and a handle extending up from the base. The enclosure component is formed of a flexible material and defines an enclosed interior space for holding a payload. The first structure component is formed of a second material and has a predetermined shape. The first structure component is secured to the enclosure component and defines at least a portion of a shape of the package.
B64D 1/08 - Largage ou éjection d'objets les objets étant des dispositifs porte-charges
B64U 10/20 - Aéronefs à décollage et atterrissage verticaux [ADAV, en anglais VTOL]
B64U 101/64 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis
73.
Dynamic UAV Transport Tasks for Pickup and Delivery of Non-Specifically Assigned 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 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
A technique for detection of an obstacle by a UAV includes arriving above a location at a first altitude by the UAV; navigating a descent flight pattern from the first altitude towards the location; acquiring aerial images of the location below the UAV with a camera system disposed onboard the UAV; and analyzing the aerial images with a machine vision system disposed onboard the UAV that is adapted to detect a presence of the obstacle in the aerial images. The descent flight pattern is selected to increase perception by the machine vision system of the obstacle.
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
B64U 101/64 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis
A technique for detection of an obstacle by a UAV includes arriving above a location at a first altitude by the UAV; navigating a descent flight pattern from the first altitude towards the location; acquiring aerial images of the location below the UAV with a camera system disposed onboard the UAV; and analyzing the aerial images with a machine vision system disposed onboard the UAV that is adapted to detect a presence of the obstacle in the aerial images. The descent flight pattern is selected to increase perception by the machine vision system of the obstacle.
A method includes receiving, at a user device, a user selection entered into a third-party application to have a payload delivered to a delivery location via an uncrewed aerial vehicle (UAV). The method also includes displaying, by the user device within the third-party application, a first UI portion of a delivery software development kit (SDK). The first UI portion enables user selection of a delivery point at the delivery location. The method additionally includes after user selection of the delivery point, receiving, at the user device, a delivery status update from the delivery SDK indicating that the UAV has commenced delivery of the payload. The method also includes displaying, by the user device within the third-party application, a second UI portion of the delivery SDK. The second UI portion displays UAV tracking information as the UAV delivers the payload to the selected delivery point at the delivery location.
A package adapted for use with an uncrewed aerial vehicle (UAV) is provided. The package includes a hanger, an enclosure component and a first structure component. The hanger includes a base and a handle extending up from the base. The enclosure component is formed of a flexible material and defines an enclosed interior space for holding a payload. The first structure component is formed of a second material and has a predetermined shape. The first structure component is secured to the enclosure component and defines at least a portion of a shape of the package.
B65D 5/42 - Détails des réceptacles ou des flans de réceptacles pliables ou dressables
B65D 5/18 - Réceptacles de section transversale polygonale rigides ou semi-rigides, p. ex. boîtes, cartons ou plateaux, formés en pliant ou montant un ou plusieurs flans de papier en pliant en forme d'U une seule feuille pour former la base du réceptacle et les côtés opposés du corps, les autres côtés étant principalement formés par les prolongements d'un ou plusieurs des côtés opposés p. ex. pattes articulées sur ceux-ci
B65D 88/14 - Grands réceptacles rigides spécialement conçus pour le transport par air
B64D 1/22 - Enlèvement d'objets à la surface du sol
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
79.
Backup Navigation System for Unmanned Aerial Vehicles
Described is a method that involves operating an unmanned aerial vehicle (UAV) to begin a flight, where the UAV relies on a navigation system to navigate to a destination. During the flight, the method involves operating a camera to capture images of the UAV's environment, and analyzing the images to detect features in the environment. The method also involves establishing a correlation between features detected in different images, and using location information from the navigation system to localize a feature detected in different images. Further, the method involves generating a flight log that includes the localized feature. Also, the method involves detecting a failure involving the navigation system, and responsively operating the camera to capture a post-failure image. The method also involves identifying one or more features in the post-failure image, and determining a location of the UAV based on a relationship between an identified feature and a localized feature.
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
G01C 11/06 - Restitution des photos par comparaison de plusieurs photos de la même zone
G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
G01C 21/32 - Structuration ou formatage de données cartographiques
G06V 20/17 - Scènes terrestres transmises par des avions ou des drones
80.
AUTOMATIC SELECTION OF DELIVERY ZONES USING SURVEY FLIGHT 3D SCENE RECONSTRUCTIONS
A method includes navigating, by an uncrewed aerial vehicle (UAV), to a delivery location in an environment. The method also includes capturing, by at least one sensor on the UAV, sensor data representative of the delivery location. The method further includes determining, based on the sensor data representative of the delivery location, a segmented point cloud. The segmented point cloud defines a point cloud of the delivery location segmented into a plurality of point cloud areas with corresponding semantic classifications. The method additionally includes determining, based on the segmented point cloud, at least one delivery point in the delivery location. The at least one delivery point in the delivery location satisfies at least one condition indicating that a descent path above the at least one delivery point represented in the point cloud is at least a particular lateral distance away from point cloud areas with corresponding semantic classifications indicative of an obstacle at the delivery location. The method also includes transmitting, by the UAV, the at least one delivery point to a server device.
A combination payload retrieval and package pickup 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 and configured to direct a payload coupling apparatus to the payload holder, a package receptacle housing having package receptacles configured to house a package to be picked up, wherein each of the package receptacles includes a locking feature to secure a package to be picked up in the package receptacle, wherein the locking feature is configured to be unlocked upon receipt of a first access code to allow access to an interior of the package receptacle to allow a package to be placed into, or removed from, the package receptacle.
A47G 29/30 - Accessoires, p. ex. dispositifs avertisseurs, lampes, moyens pour laisser des messages
A47G 29/14 - Récipients pour déposer des aliments, p. ex. petit déjeuner, laitRécipients similaires pour colis avec accessoires pour éviter que les articles déposés ne soient indûment retirés
B64F 1/32 - Installations au sol ou installations pour ponts d'envol des porte-avions pour la manutention du fret
B64D 1/22 - Enlèvement d'objets à la surface du sol
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
A UAV inchiding a wing attached to a fuselage body, a rotatable cargo bay in the fuselage body, the cargo bay having an entrance for receiving the payload, an actuator in the fuselage body operable to rotate the cargo bay about a pivot axis into a first position where the entrance of the cargo bay is positioned above the fuselage body to allow for entry of the payload into the cargo bay, and the cargo bay extends through an opening in an upper surface of the fuselage body, rotatable into a second position where the entrance of the cargo bay is positioned within the fuselage body during transport; and rotatable into a third position where the entrance of the cargo bay is positioned below the fuselage body to allow for exiting of the payload, and the cargo bay extends through an opening in a lower surface of the fuselage body.
B64U 101/60 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes
A payload retrieval apparatus having a base, an extending member secured to the base, the extending member including a lower section that is attached to the base and an upper section coupled to the lower section and movable between a first lowered position and a second raised position, an autoloader assembly mounted to the upper section of the extending member, the autoloader assembly including a payload holder configured to hold a payload for retrieval by an uncrewed aerial vehicle (UAV), a channel coupled to the payload holder and configured to direct a payload coupling apparatus to the payload holder, and a first tether engager that extends away from the channel in a first direction, wherein the first tether engager is adapted to guide a tether having a first end attached to the UAV and a second end attached to the payload coupling apparatus towards the payload holder.
A payload retrieval apparatus having an extending member having an upper end and a lower end, a channel having a first end and a second end and first and second inner edges defining a tether slot therebetween, wherein the tether slot is configured to guide passage of a tether coupled to a payload retriever suspended from a UAV when the payload retriever is passing within the channel, a first tether engager that extends in a first direction from the first end of the channel adapted to guide the tether towards the channel, a payload holder positioned near the second end of the channel that is adapted to secure a payload, wherein the channel includes a first projection that extends from the first edge into the tether slot so as to hinder removal of the tether from exiting the tether slot once the tether has entered the tether slot.
A method includes receiving, at a user device, a user selection entered into a third-party application to have a payload delivered to a delivery location via an uncrewed aerial vehicle (UAV). The method also includes displaying, by the user device within the third-party application, a first UI portion of a delivery software development kit (SDK). The first UI portion enables user selection of a delivery point at the delivery location. The method additionally includes after user selection of the delivery point, receiving, at the user device, a delivery status update from the delivery SDK indicating that the UAV has commenced delivery of the payload. The method also includes displaying, by the user device within the third-party application, a second UI portion of the delivery SDK. The second UI portion displays UAV tracking information as the UAV delivers the payload to the selected delivery point at the delivery location.
B64U 101/64 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis
87.
PAYLOAD RETRIEVAL APPARATUS WITH EXTENDING MEMBER FOR USE WITH A UAV
A payload retrieval apparatus having a base, an extending member secured to the base, the extending member including a lower section that is attached to the base and an upper section coupled to the lower section and movable between a first lowered position and a second raised position, an autoloader assembly mounted to the upper section of the extending member, the autoloader assembly including a payload holder configured to hold a payload for retrieval by an uncrewed aerial vehicle (UAV), a channel coupled to the payload holder and configured to direct a payload coupling apparatus to the payload holder, and a first tether engager that extends away from the channel in a first direction, wherein the first tether engager is adapted to guide a tether having a first end attached to the UAV and a second end attached to the payload coupling apparatus towards the payload holder.
B64F 1/32 - Installations au sol ou installations pour ponts d'envol des porte-avions pour la manutention du fret
B64D 1/22 - Enlèvement d'objets à la surface du sol
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
88.
PAYLOAD RETRIEVAL APPARATUS HAVING TETHER SLOT PROJECTION FOR USE WITH A UAV
A payload retrieval apparatus having an extending member having an upper end and a lower end, a channel having a first end and a second end and first and second inner edges defining a tether slot therebetween, wherein the tether slot is configured to guide passage of a tether coupled to a pay load retriever suspended from a UAV when the payload retriever is passing within the channel, a first tether engager that extends in a first direction from the first end of the channel adapted to guide the tether towards the channel, a pay load holder positioned near the second end of the channel that is adapted to secure a payload, wherein the channel includes a first projection that extends from the first edge into the tether slot so as to hinder removal of the tether from exiting the tether slot once the tether has entered the tether slot.
B64F 1/32 - Installations au sol ou installations pour ponts d'envol des porte-avions pour la manutention du fret
B64D 1/22 - Enlèvement d'objets à la surface du sol
B64U 101/67 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes les véhicules aériens sans pilote comprenant des attaches pour descendre les marchandises
89.
Payload retrieval apparatus with internal unlocking feature and security features for use with a UAV
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 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis au retrait de colis
90.
Combination Payload Retrieval and Package Pickup Apparatus for Use with a UAV
A combination payload retrieval and package pickup 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 and configured to direct a payload coupling apparatus to the payload holder, a package receptacle housing having package receptacles configured to house a package to be picked up, wherein each of the package receptacles includes a locking feature to secure a package to be picked up in the package receptacle, wherein the locking feature is configured to be unlocked upon receipt of a first access code to allow access to an interior of the package receptacle to allow a package to be placed into, or removed from, the package receptacle.
In some embodiments, a method of determining an estimated location of a UAV is provided. A captured image is received from a camera of the UAV. Semantic labels are generated by the UAV for a plurality of objects visible in the captured image. The UAV compares the semantic labels to reference labels associated with a reference map to determine a current location estimate. The UAV updates an accumulated location estimate using the current location estimate, and the UAV determines the estimated location of the UAV based on the accumulated location estimate.
A payload retrieval apparatus including a support structure having an upper end and a lower end; a first sloped surface secured to the support structure and a second sloped surface positioned adjacent the first sloped surface; an opening between the first and second sloped surfaces leading to a space to allow a payload retriever attached to a tether suspended from a UAV to travel into the space; an angled channel positioned beneath the first sloped surface having a tether slot to allow for passage of the tether as the payload retriever is drawn through the angled channel; and a payload holder positioned at the end of the angled channel.
B64D 1/22 - Enlèvement d'objets à la surface du sol
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
B64U 101/00 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques
B64U 101/66 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis au retrait de colis
A landing gear assembly for an unmanned aerial vehicle (UAV) includes a shock tower, a pair of leg members, and suspension assemblies. The shock tower is adapted to mount to a frame of a fuselage of the UAV and includes upper and lower end mounts. The leg members are adapted to extend out from opposing sides of the lower end mounts. The leg members are flexible and each include an upper leg section pivotally mounted to the lower end mount and a lower leg section adapted to connect to a ground gear. The suspension assemblies are each mounted to and extend between the upper end mount and a corresponding one of the leg members. The suspension assemblies each include a damper and a spring.
B64U 60/50 - Trains d’atterrissage avec jambes d’atterrissage
B64C 25/34 - Trains d'atterrissage caractérisés par les éléments de contact avec le sol ou une surface analogue du type à roues, p. ex. bogies à roues multiples
In some embodiments, a method of determining an estimated location of a UAV is provided. A captured image is received from a camera of the UAV. Semantic labels are generated by the UAV for a plurality of objects visible in the captured image. The UAV compares the semantic labels to reference labels associated with a reference map to determine a current location estimate. The UAV updates an accumulated location estimate using the current location estimate, and the UAV determines the estimated location of the UAV based on the accumulated location estimate.
A technique for detecting and avoiding obstacles by an unmanned aerial vehicle (UAV) includes: querying a knowledge graph having information related to a dynamic obstacle that may be in proximity to the UAV when traveling along a planned route; comparing the location of the dynamic obstacle to the UAV to detect conflicts; and in response to detecting a conflict, performing an action to avoid conflict with the dynamic obstacle. The knowledge graph can be updated by receiving a VHF radio signal containing the information related to the dynamic obstacle in the audible speech format; translating the audible speech format to a text format using speech recognition; analyzing the text format for relevant information related to the dynamic obstacle; comparing the relevant information related to the dynamic obstacle of the text format to the knowledge graph to detect changes; and updating the knowledge graph.
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
B64U 101/64 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de passagersVéhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques au transport de marchandises autres que des armes à la livraison ou au retrait de colis
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
96.
AUTONOMOUS DETECT AND AVOID FROM SPEECH RECOGNITION AND ANALYSIS
A technique for detecting and avoiding obstacles by an unmanned aerial vehicle (UAV) includes: querying a knowledge graph having information related to a dynamic obstacle that may be in proximity to the UAV when traveling along a planned route; comparing the location of the dynamic obstacle to the UAV to detect conflicts; and in response to detecting a conflict, performing an action to avoid conflict with the dynamic obstacle. The knowledge graph can be updated by receiving a VHF radio signal containing the information related to the dynamic obstacle in the audible speech format; translating the audible speech format to a text format using speech recognition; analyzing the text format for relevant information related to the dynamic obstacle; comparing the relevant information related to the dynamic obstacle of the text format to the knowledge graph to detect changes; and updating the knowledge graph.
G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p. ex. utilisant des pilotes automatiques
97.
Context-based navigation of uncrewed vehicles using relative position markers
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 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 die 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.
G01C 23/00 - Instruments combinés indiquant plus d’une valeur de navigation, p. ex. pour l’aviationDispositifs de mesure combinés pour mesurer plusieurs variables du mouvement, p. ex. la distance, la vitesse ou l’accélération
G01C 15/02 - Moyens pour marquer les points de mesure
G01C 21/00 - NavigationInstruments de navigation non prévus dans les groupes
B64U 20/87 - Montage des dispositifs d’imagerie, p. ex. montage des suspensions à cardan
An unmanned aerial vehicle (UAV) includes a propulsion system, a global navigation satellite system (GNSS) sensor, a camera and a controller. The controller includes logic that, in response to execution by the controller, causes the UAV to in response to detecting a loss of tracking by the GNSS sensor determine an estimated location of the UAV on a map based on a location image captured by the camera, determine a route to a destination using tracking parameters embedded in the map, wherein the map is divided into a plurality of sections and the tracking parameters indicate an ease of determining a location of the UAV using images captured by the camera with respect to each section, and control the propulsion system to cause the UAV to follow the route to the destination.
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
G05D 1/222 - Dispositions de commande à distance actionnées par des humains
G05D 1/225 - Dispositions de commande à distance actionnées par des ordinateurs externes
G05D 1/689 - Interaction avec des charges utiles ou des entités externes dirigeant des charges utiles vers des cibles fixes ou en mouvement
H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
100.
SYSTEMS, METHODS, AND APPARATUS FOR TESTING UAV DEVICES
Systems, apparatus, and methods are presented for testing a device. One method includes activating an actuator device to cause a. carriage, coupled to a device, to be moved in one or more directions along a guide rail, wherein the device includes at least one processing device and one or more sensor devices. The method may also comprise receiving, by the device, one or more input commands and executing, by the device based on the one or more input commands, a. software application to generate an output while the device is moving in the one or more directions. Further, the method may comprise verifying the execution of the software application on the device based on the output.
