Amazon Technologies, Inc.

Nathan Michael Paczan

Daniel Buchmueller

Michael John Elzinga

Luan Khai Nguyen

Raphael Hsieh

This disclosure describes a collective UAV in which multiple UAVs may be coupled together to form the collective UAV. A collective UAV may be used to aerially transport virtually any size, weight or quantity of items, travel longer distances, etc. For example, rather than using one large UAV to carry a larger or heavier item, multiple smaller UAVs may couple together to form a collective UAV that is used to carry the larger or heavier item.

Collective unmanned aerial vehicle configurations

Techniques for managing a flow of an unmanned vehicle within a space may be described. In particular, the unmanned vehicle may be determined as being location within the space. The space may be associated with metric that may be based on a plurality of other unmanned vehicles also located within the space. Pairs of location and time data may be computed for the unmanned vehicle. The pairs may represent a path for the unmanned vehicle to use within the space. The pairs of location data and time data computed based on data associated with the unmanned vehicle, data associated with at least one of the other unmanned vehicles, and the metric associated with the space. Once computed, the pairs may be provided to the unmanned vehicle.

Managing unmanned vehicles

This disclosure is directed to a detection and avoidance apparatus for an unmanned aerial vehicle ('UAV') and systems, devices, and techniques pertaining to automated object detection and avoidance during UAV flight. The system may detect objects within the UAV's airspace through acoustic, visual, infrared, multispectral, hyperspectral, or object detectable signal emitted or reflected from an object. The system may identify the source of the object detectable signal by comparing features of the received signal with known sources signals in a database. The features may be, for example, a light arrangement or number of lights associated with the object. Furthermore, a trajectory envelope for the object may be determined based on characteristic performance parameters for the object such as cursing speed, maneuverability, etc. The UAV may determine an optimized flight plan based on the trajectory envelopes of detected objects within the UAV's airspace to avoid the detected objects.

Multi-zone montoring systems and methods for detection and avoidance of objects by an unmaned aerial vehicle (UAV)

This disclosure is directed to a detection and avoidance apparatus for an unmanned aerial vehicle ('UAV') and systems, devices, and techniques pertaining to automated object detection and avoidance during UAV flight. The system may detect objects within the UAV's airspace through acoustic, visual, infrared, multispectral, hyperspectral, or object detectable signal emitted or reflected from an object. The system may identify the source of the object detectable signal by comparing features of the received signal with known sources signals in a database. The features may include, for example, an acoustic signature emitted or reflected by the object. Furthermore, a trajectory envelope for the object may be determined based on characteristic performance parameters for the object such as cursing speed, maneuverability, etc. The UAV may determine an optimized flight plan based on the trajectory envelopes of detected objects within the UAV's airspace.

Systems and methods for unmanned aerial vehicle object avoidance

This disclosure is directed to a detection and avoidance apparatus for an unmanned aerial vehicle ('UAV') and systems, devices, and techniques pertaining to automated object detection and avoidance during UAV flight. The system may detect objects within the UAV's airspace through acoustic, visual, infrared, multispectral, hyperspectral, or object detectable signal emitted or reflected from an object. The system may identify the source of the object detectable signal by comparing features of the received signal with known sources signals in a database. The features may include, for example, a multispectral signature emitted or reflected by the object. Furthermore, a trajectory envelope for the object may be determined based on characteristic performance parameters for the object such as cursing speed, maneuverability, etc. The UAV may determine an optimized flight plan based on the trajectory envelopes of detected objects within the UAV's airspace.

Commercial and general aircraft avoidance using multi-spectral wave detection

This disclosure provides egress and ingress for unmanned aerial vehicles (UAVs) from a fulfillment center (FC) to perform deliveries of products and return to the FC from such deliveries while providing minimal exposure of an interior of the FC. The UAV may be used to deliver the cargo from the FC to a destination, and then return to the FC to retrieve other cargo for another transport to another destination. In some embodiments, departing UAVs may be launched from the FC through a launch bay and returning UAVs may land upon a conveyance system to await being transported back into the FC. A flight coordinator may also provide assignments to the UAV based upon a current state of the UAV and other nearby UAVs and also based on a current order backlog of the FC and/or other considerations.

Unmanned aerial vehicle secure egress and ingress

Commercial and general aircraft avoidance using light pattern detection

This disclosure is directed to a detection and avoidance apparatus for an unmanned aerial vehicle ('UAV') and systems, devices, and techniques pertaining to automated object detection and avoidance during UAV flight. The system may detect objects within the UAV's airspace through acoustic, visual, infrared, multispectral, hyperspectral, or object detectable signal emitted or reflected from an object. The system may identify the source of the object detectable signal by comparing features of the received signal with known sources signals in a database. The features may include, for example, an acoustic signature emitted or reflected by the objet. Furthermore, a trajectory envelope for the object may be determined based on characteristic performance parameters for the object such as cursing speed, maneuverability, etc. The UAV may determine an optimized flight plan based on the trajectory envelopes of detected objects within the UAV's air-space.

Growing community of inventors

Seattle, WA, United States of America

Nathan Michael Paczan