Amazon Technologies, Inc.

Scott Patrick Boyd

Joshua John Watson

Barry James O'Brien

Scott Michael Wilcox

Chengwu Luke Cui

Sarah Graber

Benjamin Novak

Benjamin Israel Caro

Techniques for verifying a location and identification of a landing marker to aid an unmanned aerial vehicle (UAV) to deliver a payload to a location may be provided. For example, upon receiving an indication that a UAV has arrived to a delivery location, a server computer may process one or more images of an area that are provided by the UAV and/or a user interacting with a user device. A landing marker may be identified in the image and a representation of the landing marker along with instructions to guide the UAV to deliver the payload to the landing marker may be transmitted to the UAV and implemented by the UAV.

Drone marker and landing zone verification

Camera calibration may be performed in a mobile environment. One or more cameras can be mounted on a mobile vehicle, such as an unmanned aerial vehicle (UAV) or an automobile. Because of the mobility of the vehicle the one or more cameras may be subjected to inaccuracy in imagery caused by various factors, such as environmental factors (e.g., airflow, wind, etc.), impact by other objects (e.g., debris, vehicles, etc.), vehicle vibrations, and the like. To reduce the inaccuracy in imagery, the mobile vehicle can include a mobile camera calibration system configured to calibrate the one or more cameras while the mobile vehicle is traveling along a path. The mobile camera calibration system can cause the one or more cameras to capture an image of an imaging target while moving, and calibrate the one or more cameras based on a comparison between the image and imaging target data.

Camera calibration in a mobile environment

A propeller provided on an aerial vehicle may include a digital camera or other imaging device embedded into a surface of one of the blades of the propeller. The digital camera may capture images while the propeller is rotating at an operational speed. Images captured by the digital camera may be processed to recognize one or more objects therein, and to determine ranges to such objects by stereo triangulation techniques. Using such ranges, a depth map or other model of the surface features in an environment in which the aerial vehicle is operating may be defined and stored or used for any purpose. A propeller may include digital cameras or other imaging devices embedded into two or more blades, and may also use such images to determine ranges to objects by stereo triangulation techniques.

Determining stereo distance information using imaging devices integrated into propeller blades

Systems and methods for detecting contamination on a sensor cover. In an example, an image sensor of a vehicle may be used to capture an image of an environment of the vehicle. A sensor cover may be positioned outwardly from the image sensor and may form a covered volume around at least a sensing surface of the image sensor. A light source may be positioned in the covered volume. A management module may be coupled with the image sensor. The management module may be configured to receive test image data of the environment generated by the image sensor while the light source is on, compare the test image data to baseline image data generated while the light source is off, and detect whether contamination exists on a surface of the sensor cover based on the comparison.

Vehicle camera contamination detection

A location marker that may be used to provide information to a vehicle, such as an unmanned aerial vehicle (UAV). The location marker may include a plurality of retroreflectors that may form a pattern readable by a vehicle or other device. The pattern may be read to extract an identifier of a location, such as an address or an identifier of a person. A global positioning system (GPS) device may transmit a general location of the location marker to the vehicle, while the location marker may provide a unique visual location identifier to a device within visual range of the location marker. In some embodiments, the location marker may also include lights that may be individually sequenced on and off at different times to create a time domain signal sequence that is readable by the vehicle.

Location marker with retroreflectors

Techniques for providing an object awareness guidance to clear a landing space may be provided. For example, during delivery an unmanned aerial vehicle (UAV) may capture an image of a potential landing zone and identify one or more objects in the image that may impede or obstruct delivery of the item in the potential landing zone. The UAV may be configured to generate and provide instructions to a user device to move or remove the identified one or more objects from the potential landing zone thereby creating a safe and unobstructed landing zone to deliver the item.

Obstacle awareness based guidance to clear landing space

A location marker that may be used to provide information to a vehicle, such as an unmanned aerial vehicle (UAV). The location marker may include a plurality of lights that may be individually sequenced on and off at different times to create a time domain signal sequence that is readable by the vehicle. The lights may provide information in various different ways. The specific lights that are illuminated at a certain time may form a light pattern that includes or is associated with information. Different light patterns may be displayed over time to provide different information to the vehicle. In some embodiments, the amount of time that a light is on or off (or both) may provide information as a time domain signal sequence (e.g., flashing lights) to the vehicle. In various embodiments, the location marker may include retroreflectors arranged in a pattern used to identify the location marker.

Location marker with lights

Systems and methods are provided herein for detecting a marker (e.g., a marker that identifies a delivery location) utilizing an image captured by a camera of an unmanned aerial vehicle. A method may include obtaining marker information associated with a marker, the marker comprising a repetitive visual pattern, the marker being associated with delivery of an item by an unmanned aerial vehicle. Optical pattern information may be obtained that indicates a moir&#xe9; pattern associated with the marker and the one or more cameras of the unmanned aerial vehicle. Image capture information that is associated with an image comprising the marker may be received. The marker may be detected in the image based at least in part on the image capture information and the moir&#xe9; pattern associated with the marker.

Techniques for target detection

Techniques for providing a verification of a flight path or landing zone may be provided. For example, during delivery an unmanned aerial vehicle (UAV) may capture one or more images of a plurality of delivery locations within an area. A computer system may generate one or more image templates or filters using the one or more images and subsequently use the image filters to verify a flight path or landing zone for a delivery by the UAV during flight.

Drone location signature filters

This disclosure describes systems, methods, and apparatus for automating the verification of aerial vehicle sensors as part of a pre-flight, flight departure, in-transit flight, and/or delivery destination calibration verification process. At different stages, aerial vehicle sensors may obtain sensor measurements about objects within an environment, the obtained measurements may be processed to determine information about the object, as presented in the measurements, and the processed information may be compared with the actual information about the object to determine a variation or difference between the information. If the variation is within a tolerance range, the sensor may be auto adjusted and operation of the aerial vehicle may continue. If the variation exceeds a correction range, flight of the aerial vehicle may be aborted and the aerial vehicle routed for a full sensor calibration.

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Seattle, WA, United States of America

Scott Patrick Boyd