Amazon Technologies, Inc.

Other

Steven Gregory Dunn

Brian C Beckman

Avi Bar-Zeev

Neil Whitney Woodward, Iii

Carl Ryan Kelso

Amir Navot

Gur Kimchi

Daniel Buchmueller

Atishkumar Kalyan

Frederik Schaffalitzky

Techniques for facilitating an autonomous operation, such as an autonomous navigation, of an unmanned vehicle based on one or more fiducials. For example, image data of a fiducial may be generated with an optical sensor of the unmanned vehicle. The image data may be analyzed to determine a location of the fiducial. A location of the unmanned vehicle may be estimated from the location of the fiducial and the image. The autonomous navigation of the unmanned vehicle may be directed based on the estimated location.

Fiducial-based navigation of unmanned vehicles

Disclosed are methods and systems for delivery of items using an unmanned aerial vehicle ('UAV'). A user may be provided with a delivery location identifier ('DLI') that is to be placed at a delivery location within a delivery destination to identify where a UAV is to position an item as part of a delivery to the delivery destination. For example, the delivery destination may be a user's home. Within the deliver destination of the user's home, the user may select a delivery location, such as a spot in the back yard wherein the UAV is to position the ordered item as part of the delivery. To aid the UAV in navigating to the delivery location, the user places the DLI at the delivery location. The UAV detects the DLI and positions the item at or near the DLI as part of the item delivery.

Delivery location identifiers

Systems and methods for providing a multi-direction wind tunnel, or 'windball,' are disclosed. The system can have a series of fans configured to provide air flow in a plurality of directions to enable accurate testing of aircraft, unmanned aerial vehicles (UAVs), and other vehicles capable of multi-dimensional flight. The system can comprise a spherical or polyhedral test chamber with a plurality of fans. The fans can be arranged in pairs, such that a first fan comprises an intake fan and a second fan comprises an exhaust fan. The direction of the air flow can be controlled by activating one or more pairs of fans, each pair of fan creating a portion of the air flow in a particular direction. The direction of the air flow can also be controlled by rotating one or more pairs of fans with respect to the test chamber on a gimbal device, or similar.

Multi-faceted test chamber

A transportation network is provided that utilizes autonomous vehicles (e.g., unmanned aerial vehicles) for identifying, acquiring, and transporting items between network locations without requiring human interaction. A travel path for an item through the transportation network may include multiple path segments and corresponding intermediate network locations, with a different autonomous vehicle utilized to transport the item along each path segment. Different possible next network locations for a travel path may selected based on transportation factors such as travel time, cost, safety, etc. (e.g., as may be related to distance, network congestion, inclement weather, etc.). Local processing (e.g., by a control system of an autonomous vehicle) may perform the selection of a next network location for a travel path (e.g., allowing multiple autonomous vehicles to simultaneously engage and depart with items or otherwise travel without having to contact and wait for instructions from centralized system components, etc.).

Transportation network utilizing multiple autonomous vehicles to transport items between network locations

A transportation network is provided that utilizes autonomous vehicles (e.g., unmanned aerial vehicles) for identifying, acquiring, and transporting items between network locations without requiring human interaction. A travel path for an item through the transportation network may include a passing of the item from one autonomous vehicle to another or otherwise utilizing different autonomous vehicles for transporting the item along different path segments (e.g., between different network locations). Different possible travel paths through the transportation network may be evaluated, and a travel path for an item may be selected based on transportation factors such as travel time, cost, safety, etc., which may include consideration of information regarding current conditions (e.g., related to network congestion, inclement weather, etc.). Autonomous vehicles of different sizes, carrying capacities, travel ranges, travel speeds, etc. may be utilized for further improving the flexibility and efficiency of the system for transporting items.

Transportation network utilizing autonomous vehicles for transporting items

Some examples include an inventory system having both mobile drive units remotely controllable to transport inventory items and holders within a warehouse and automated aerial vehicles remotely controllable to identify and remove amnesty items from the storage region. In some implementations, the automated aerial vehicles are equipped with imaging components to monitor the floor of the warehouse to identify and engagement mechanisms to secure and remove the amnesty items that may otherwise impede the movement of the mobile drive units.

Growing community of inventors

Bothell, WA, United States of America

Steven Gregory Dunn