Abstract: 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.

Abstract: This disclosure describes a configuration of an aerial vehicle, such as an unmanned aerial vehicle (“UAV”), that includes a plurality of cameras that may be selectively combined to form a stereo pair for use in obtaining stereo images that provide depth information corresponding to objects represented in those images. Depending on the distance between an object and the aerial vehicle, different cameras may be selected for the stereo pair based on the baseline between those cameras and a distance between the object and the aerial vehicle. For example, cameras with a small baseline (close together) may be selected to generate stereo images and depth information for an object that is close to the aerial vehicle. In comparison, cameras with a large baseline may be selected to generate stereo images and depth information for an object that is farther away from the aerial vehicle.

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: 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.

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: This disclosure describes a configuration of an aerial vehicle, such as an unmanned aerial vehicle (“UAV”), that includes a plurality of cameras that may be selectively combined to form a stereo pair for use in obtaining stereo images that provide depth information corresponding to objects represented in those images. Depending on the distance between an object and the aerial vehicle, different cameras may be selected for the stereo pair based on the baseline between those cameras and a distance between the object and the aerial vehicle. For example, cameras with a small baseline (close together) may be selected to generate stereo images and depth information for an object that is close to the aerial vehicle. In comparison, cameras with a large baseline may be selected to generate stereo images and depth information for an object that is farther away from the aerial vehicle.

Abstract: Systems, apparatuses, and methods provide simulations to vehicles, such as unmanned aerial vehicles (UAVs) equipped with stereoscopic cameras. The system can include a plurality of screens set at predetermined angles to provide proper parallax to the stereoscopic cameras. The system can also include a test computer to update the screens based on the actions and travel time of the UAV. The test computer can also monitor the load on the computing systems of the UAV due to the camera and other inputs. The system can enable the testing and configuration of cameras and sensors without requiring actual flight. The test computer can provide navigational information to the UAV, receive actions taken by the UAV, update the screens based on these actions and the travel speed and direction of the UAV, and monitor the effects of the cameras and other sensors on the internal components of the UAV during use.

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: This disclosure is directed to monitoring exposure levels for individual cameras of a stereo camera system to reduce unwanted lens flaring which may disrupt stereo vision capabilities of an unmanned aerial vehicle (UAV). The UAV may identify lens flaring by monitoring histogram data received from the cameras and then mitigate the lens flaring by performing aerial maneuvers with respect to the light source and/or moving camera componentry such as deploying a lens hood. The UAV may also identify lens flaring patterns that on a camera's sensor and determine a location of a peripheral light source based on these patterns. The UAV may then deploy a visor between the location of the peripheral light source and the cameras.

Abstract: Images captured by a camera system of an unmanned aerial vehicle (UAV) can be used to determine a weather condition in an environment of the UAV. The camera system of the UAV can capture one or more images, and a characteristic of at least one image of the one or more images can be determined from image data associated with the at least one image. A weather condition of the environment of the UAV can be determined based at least in part on the characteristic of the at least one image.

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 configurable unmanned aerial vehicle (UAV) may include swappable components that may be selectable to configure a customized UAV just prior to deployment of the UAV that is configured to deliver a package to a destination. The UAV may include a plurality of ports that may accept swappable components. The ports may be coupled to a logic board to enable control of the swappable components. The ports and swappable components may enable quick replacement of a malfunctioning components, such as an image sensor, which may avoid subjecting a UAV to significant downtime for service. The malfunctioning component may then be serviced after the UAV is readied for a subsequent flight or deployed on a subsequent flight.

Abstract: A mobile calibration room may be used for calibrating one or more sensors used on unmanned aerial vehicles (UAVs). A system can include folding or collapsible walls to enable the system to be moved between a stowed position and a deployed position. In the deployed position, the system can comprise a calibration room including one or more 2D or 3D targets used to calibrate one or more sensors (e.g., cameras) on a UAV. The system can include a turntable to rotate the UAV about a first axis during calibration. The system can also include a cradle to rotate the UAV around, or translate the UAV along, a second axis. The turntable can include a frame to rotate the UAV around a third axis during calibration. The mobile calibration room can be coupled to a vehicle to enable the mobile calibration room to be moved between locations.

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: 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: Aerial vehicles may include one or more directional sensors embedded into wings, rudders, ailerons, flaps or other control surfaces. When the aerial vehicles are operating in modes that do not require the use of such surfaces, a surface having a directional sensor embedded therein may be repositioned or reoriented to align the directional sensor toward an area or axis of interest, and information may be gathered from the area or axis of interest using the directional sensor. One or more safety lights, running lights or other illuminators may cast light of a desired color, frequency or wavelength toward the area or axis of interest. The directional sensors may include cameras, radar or laser sensors, or any other reorientable sensors.

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: 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.

Abstract: A method, device, and system for detecting transparent elements in a vehicle environment are described. In some examples, this may include accessing a first image depicting a scene. The first image may include a first polarization characteristic. A second image depicting the scene may also be accessed. The second image may include a second polarization characteristic. It may be determined that the scene includes an element having transparent properties based at least in part on the first image and the second image.