Amazon Technologies, Inc.

Microsoft Technology Licensing, LLC

Other

The United States of America As Represented by the Administrator of the

Brian C Beckman

Gur Kimchi

Henricus Johannes Maria Meijer

Amir Navot

Daniel Buchmueller

Fabian Hensel

Allan Ko

Brandon William Porter

Scott A Green

Avi Bar-Zeev

Vijay Mital

Darryl Ellis Rubin

Frederik Schaffalitzky

Severan Sylvain Jean-Michel Rault

Scott M Isaacs

Corrinne Yu

Avner Y Aharoni

Amanda K Silver

Paul Allen Vick, Jr

David N Schach

Jack Erdozain, Jr

Michael Rolnik

Nicholas Bjone

Ricky Dean Welsh

Emmanouil Koukoumidis

Anthony Dean Andrews

Peter Drayton

Menashe Haskin

Atishkumar Kalyan

Vedran Coralic

John Raymond Brodie

Dominic Timothy Shiosaki

Jeffrey Van Gogh

David G Green

Richard Philip Whitlock

Nicholas Hampel Roberts

Ralf Lammel

Lucius Gregory Meredith

Taylor David Grenier

Steven Gregory Dunn

Michael Vogelsong

Marc Levy

Benjamin Lev Snyder

Berk Ozturk

Leonardo Ruggiero Bachega

Jeffrey P Bezos

Louis LeRoi LeGrand, Iii

Olivier Colle

Eran Yariv

Amit Mital

Danny Van Velzen

John Clark Coonley Duksta

Elad Gerson

Eyal Ofek

Blaise Aguera Y Arcas

Andrew Douglas Reddish

Jason L Zander

Mark Brian Shields

Sheridan Leigh Martin

Yan Vule

Pragyana K Mishra

Bimal Kumar Mehta

Gary Shon Katzenberger

Scott Raymond Harris

Arjmand Samuel

Wei Zhu

Gershon Parent

Sumit Kumar

Robert John Anderson

Michael John Elzinga

Alexander A Armanasu

Bruno S Bozza

Konstantinos Aisopos

Anders Hejlsberg

Christopher Wellington Brumme

Scott Michael Wilcox

Suraj T Poozhiyil

Brian LaMacchia

Noam Sorek

Benjamin Livshits

Jeffrey Darren Couckuyt

Andrew Eyring Kimball

Shai Herzog

Michael Barnett

Ido Omer

Dragos A Manolescu

Barbara Lynch Fox

John Wesley Dyer

Emilia Sorana Buneci

Janine Crumb

Evgueni Zabokritski

Harish Venkata Kantamneni

Howard Lee Huddleston, Jr

Jason A Wolf

Meir Ben Itay

Norm Bryar

Selvi Chennai

Vadim Kuper

Fei H Chua

Kenn Cartier

This disclosure describes an unmanned aerial vehicle ('UAV') configured to autonomously deliver items of inventory to various destinations. The UAV may receive inventory information and a destination location and autonomously retrieve the inventory from a location within a materials handling facility, compute a route from the materials handling facility to a destination and travel to the destination to deliver the inventory.

Aerial vehicle delivery location

Intermodal vehicles may be loaded with items and an aerial vehicle, and directed to travel to areas where demand for the items is known or anticipated. The intermodal vehicles may be coupled to locomotives, container ships, road tractors or other vehicles, and equipped with systems for loading one or more items onto the aerial vehicle, and for launching or retrieving the aerial vehicle while the intermodal vehicles are in motion. The areas where the demand is known or anticipated may be identified on any basis, including but not limited to past histories of purchases or deliveries to such areas, or events that are scheduled to occur in such areas. Additionally, intermodal vehicles may be loaded with replacement parts and/or inspection equipment, and configured to conduct repairs, servicing operations or inspections on aerial vehicles within the intermodal vehicles, while the intermodal vehicles are in motion.

Distributing items using multimodal delivery systems

The disclosure describes an automated aerial vehicle (AAV) and system for automatically detecting a contact or an imminent contact between a propeller of the AAV and an object (e.g., human, pet, or other animal). When a contact or an imminent contact is detected, a safety profile may be executed to reduce or avoid any potential harm to the object and/or the AAV. For example, if a contact with a propeller of the AAV by an object is detected, the rotation of the propeller may be stopped to avoid harming the object. Likewise, an object detection component may be used to detect an object that is nearing a propeller, stop the rotation of the propeller, and/or navigate the AAV away from the detected object.

Propeller safety for automated aerial vehicles

This disclosure is directed to an unmanned aerial vehicle ('UAV') that transitions in-flight between vertical flight configuration and horizontal flight configuration by changing an orientation of the UAV by approximately ninety degrees. The UAV may include propulsion units that are coupled to a wing. The wing may include wing segments rotatably coupled together by pivots that rotate to position the propulsion units around a center of mass of the UAV when the fuselage is oriented perpendicular with the horizon. In this vertical flight configuration, the UAV may perform vertical flight or hover. During the vertical flight, the UAV may cause the wing to extend outward via the pivots such that the wing segments become positioned substantially parallel to one another and the wing resembles a conventional fixed wing. With the wing extended, the UAV assumes a horizontal flight configuration that provides upward lift generated from the wing.

In-flight reconfigurable hybrid unmanned aerial vehicle

This disclosure describes an unmanned aerial vehicle that may be configured during flight to optimize for agility or efficiency.

Adjustable unmanned aerial vehicles with adjustable body portions

A machine learning system builds and uses computer models for controlling robotic performance of a task. Such computer models may be first trained using feedback on computer simulations of the robotic system performing the task, and then refined using feedback on real-world trials of the robot performing the task. Some examples of the computer models can be trained to automatically evaluate robotic task performance and provide the feedback. This feedback can be used by a machine learning system, for example an evolution strategies system or reinforcement learning system, to generate and refine the controller.

Simulation-real world feedback loop for learning robotic control policies

Directed audio-encoded data emissions systems and methods may include one or more sensors, one or more audio transmitters, and a controller configured to cause emission of directed audio-encoded data toward various objects, such as vehicles, user devices, audio input/output devices, or others. For example, responsive to detecting a potential safety situation and/or a potential intended communication situation associated with one or more detected objects, audio-encoded data having selected audio characteristics may be emitted toward the detected objects using selected audio transmitters. The audio characteristics may be selected to encode one or more instructions to be executed by the detected objects, and the instructions may cause emission of audio, visual, or haptic notifications and/or initiation of various functions or operations by the objects.

Directed audio-encoded data emission systems and methods for vehicles and devices

Demand-based distribution of items using intermodal carriers and unmanned aerial vehicles

In-flight reconfigurable hybrid unmanned aerial vehicle with swing arm for engaging or disengaging items

Sounds are generated by an aerial vehicle during operation. For example, the motors and propellers of an aerial vehicle generate sounds during operation. Disclosed are systems, methods, and apparatus for actively adjusting the position and/or configuration of one or more propeller blades of a propulsion mechanism to generate different sounds and/or lifting forces from the propulsion mechanism.

Aerial vehicle adaptable propeller blades

An unmanned aerial vehicle (UAV) may emit masking sounds during operation of the UAV to mask other sounds generated by the UAV during operation. The UAV may be used to deliver items to a residence or other location associated with a customer. The UAV may emit sounds that mask the conventional sounds generated by the propellers and/or motors to cause the UAV to emit sounds that are pleasing to bystanders or do not annoy the bystanders. The UAV may emit sounds using speakers or other sound generating devices, such as fins, reeds, whistles, or other devices which may cause sound to be emitted from the UAV. Noise canceling algorithms may be used to cancel at least some of the conventional noise generated by operation of the UAV using inverted sounds, while additional sound may be emitted by the UAV, which may not be subject to noise cancelation.

Delivery sound masking and sound emission

In server/client architectures, the server application and client applications are often developed in different languages and execute in different environments specialized for the different contexts of each application (e.g., low-level, performant, platform-specialized, and stateless instructions on the server, and high-level, flexible, platform-agnostic, and stateful languages on the client) and are often executed on different devices. Convergence of these environments (e.g., server-side JavaScript using Node.js) enables the provision of a server that services client applications executing on the same device. The local server may monitor local events occurring on the device, and may execute one or more server scripts associated with particular local events on behalf of local clients subscribing to the local event (e.g., via a subscription model). These techniques may enable development of local event services in the same language and environment as client applications, and the use of server-side code in the provision of local event service.

Event service for local client applications through local server

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Newcastle, WA, United States of America

Brian C Beckman