Abstract: Images captured by a camera system can be processed to detect precipitation in one or more of the images, and to generate a reconstructed image(s) without the precipitation, or with a reduced amount of the precipitation. Detection of precipitation can be based on a difference between a first feature in a first image and a second feature in a second image that corresponds to the first feature, where the first and second images were captured by different cameras at different times. A determination as to whether precipitation is present in the first image and the second image can be based at least in part on a disparity between the first feature and the second feature.

Abstract: 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.

Abstract: 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 moiré 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 moiré pattern associated with the marker.

Abstract: Described is an aerial vehicle, such as an unmanned aerial vehicle (“UAV”), that includes a plurality of sensors, such as stereo cameras, mounted along a perimeter frame of the aerial vehicle and arranged to generate a scene that surrounds the aerial vehicle. The sensors may be mounted in or on winglets of the perimeter frame. Each of the plurality of sensors has a field of view and the plurality of optical sensors are arranged and/or oriented such that their fields of view overlap with one another throughout a continuous space that surrounds the perimeter frame. The fields of view may also include a portion of the perimeter frame or space that is adjacent to the perimeter frame.

Abstract: 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.

Abstract: 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.

Abstract: This disclosure describes an aerial vehicle that includes a light alteration assembly that may be used to alter light entering a lens of a camera of the aerial vehicle. The light alteration assembly may include an adjustable visor and/or filters that may be selectively positioned over the lens of the camera. By altering light entering the lens of a camera of the aerial vehicle, the camera is able to obtain higher quality images of the area surrounding the aerial vehicle. The higher quality images may then be processed to accurately detect objects within a vicinity of the aerial vehicle.

Abstract: Described is an, such as an unmanned aerial vehicle (“UAV”), that includes stereo pairs of imaging element, each imaging element including a region of interest controller. The region of interest controller for an imaging element of the stereo pair receives movement information affecting the imaging element and selects a portion of pixels of a digital image formed by the imaging element. The portion of pixels are provided to an image processor that utilizes the portion of pixels to determine depth information for objects represented by the pixels.

Abstract: Described are systems, methods, and apparatus for detecting objects within a distance of an aerial vehicle, such as an unmanned aerial vehicle (“UAV”), and developing a three-dimensional model or representation of those objects. Rather than attempting to use stereo imagery to determine distances and/or depth of objects, the described implementations utilize range-gating, also known as time-gating, and the known position of the aerial vehicle to develop a three-dimensional representation of objects. For example, when the aerial vehicle is at a first position it may use range-gating to detect an object at a defined distance from the vehicle. The aerial vehicle may then alter its position again and use range-gating to detect an object that is the defined distance from the vehicle at the new position. This may be done at several different positions and the resulting information and aerial vehicle position information combined to form a three-dimensional representation of those objects.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Described is an imaging component for use by an unmanned aerial vehicle (“UAV”) for object detection. As described, the imaging component includes one or more cameras that are configured to obtain images of a scene using visible light that are converted into a depth map (e.g., stereo image) and one or more other cameras that are configured to form images, or thermograms, of the scene using infrared radiation (“IR”). The depth information and thermal information are combined to form a representation of the scene based on both depth and thermal information.

Abstract: An unmanned aerial vehicle (UAV) may provide an approach notification to enable people to understand and interpret actions by the UAV, such as an intention to land or deposit a package at a particular location. The UAV may communicate a specific intention of the UAV and/or communicate a request to a person. The UAV may monitor the person or data signals for a response from the person, such as movement of the person that indicates a response. The UAV may be equipped with hardware and/or software configured to provide notifications and/or exchange information with a person at or near a destination. The UAV may include lights, a speaker, and possibly a projector to enable the UAV to project information and/or text on a surface. The UAV may control a moveable mechanism to “point” toward the person, at an object, or in another direction.

Abstract: 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.

Abstract: Described is an imaging component for use by an unmanned aerial vehicle (“UAV”) for object detection. As described, the imaging component includes one or more cameras that are configured to obtain images of a scene using visible light that are converted into a depth map (e.g., stereo image) and one or more other cameras that are configured to form images, or thermograms, of the scene using infrared radiation (“IR”). The depth information and thermal information are combined to form a representation of the scene based on both depth and thermal information.

Abstract: Described is an aerial vehicle, such as an unmanned aerial vehicle (“UAV”), that includes a plurality of sensors, such as stereo cameras, mounted along a perimeter frame of the aerial vehicle and arranged to generate a scene that surrounds the aerial vehicle. The sensors may be mounted in or on winglets of the perimeter frame. Each of the plurality of sensors has a field of view and the plurality of optical sensors are arranged and/or oriented such that their fields of view overlap with one another throughout a continuous space that surrounds the perimeter frame. The fields of view may also include a portion of the perimeter frame or space that is adjacent to the perimeter frame.

Abstract: 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.

Abstract: An aerial vehicle may include a first sensor, such as a digital camera, having a lens or other component that includes a second sensor mounted thereto. Information or data, such as digital images, captured using the second sensor may be used to determine or predict motion of the lens, which may include components of translational and/or rotational motion. Once the motion of the lens has been determined or predicted, such motion may be used to stabilize information or data, such as digital images, captured using the first sensor, according to optical or digital stabilization techniques. Where operations of the first sensor and the second sensor are synchronized, motion of the second sensor may be modeled based on information or data captured thereby, and imputed to the first sensor.