Abstract: A base station is disclosed for an unmanned aerial vehicle (UAV). The base station includes: an enclosure; a slide mechanism that is connected to the enclosure and which is repositionable between a retracted position and an extended position; and a cradle that is connected to the slide mechanism and which defines a chamber that is configured to receive the UAV such that the UAV is movable into and out of the enclosure during repositioning of the slide mechanism between the retracted position and the extended position. The cradle includes: an upper shell; a lower shell that is connected to the upper shell; and at least one thermal insulator that is located between the upper shell and the lower shell.

Abstract: Methods, systems, and program products of inspecting solar panels using unmanned aerial vehicles (UAVs) are disclosed. A UAV can obtain a position of the Sun in a reference frame, a location of a solar panel in the reference frame, and an orientation of the solar panel in the reference frame. The UAV can determine a viewing position of the UAV in the reference frame based on at least one of the position of the Sun, the location of the solar panel, and the orientation of the solar panel. The UAV can maneuver to the viewing position and point a thermal sensor onboard the UAV at the solar panel. The UAV can capture, by the thermal sensor, a thermal image of at least a portion of the solar panel. A server onboard the UAV or connected to the UAV can detect panel failures based on the thermal image.

Abstract: Described herein are systems for automated docking of an unmanned aerial vehicle. For example, some systems include an unmanned aerial vehicle including a propulsion mechanism, an image sensor, and processing apparatus; and a dock including a landing surface configured to hold the unmanned aerial vehicle and a fiducial on the landing surface, wherein the processing apparatus is configured to: control the propulsion mechanism to cause the unmanned aerial vehicle to fly to a first location in a vicinity of the dock; access one or more images captured using the image sensor; detect the fiducial in at least one of the one or more images; determine a pose of the fiducial based on the one or more images; and control, based on the pose of the fiducial, the propulsion mechanism to cause the unmanned aerial vehicle to land on the landing surface.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for unmanned aerial vehicle modular command priority determination and filtering system. One of the methods includes enabling control of the UAV by a first control source that provides modular commands to the UAV, each modular command being a command associated with performance of one or more actions by the UAV. Modular commands from a second control source requesting control of the UAV are received. The second control source is determined to be in control of the UAV based on priority information associated with each control source. Control of the UAV is enabled by the second control source, and modular commands are implemented.

Abstract: Autonomous aerial navigation in low-light and no-light conditions includes using night mode obstacle avoidance intelligence, training, and mechanisms for vision-based unmanned aerial vehicle (UAV) navigation to enable autonomous flight operations of a UAV in low-light and no-light environments using infrared data.

Abstract: Systems and methods are disclosed for tracking objects in a physical environment using visual sensors onboard an autonomous unmanned aerial vehicle (UAV). In certain embodiments, images of the physical environment captured by the onboard visual sensors are processed to extract semantic information about detected objects. Processing of the captured images may involve applying machine learning techniques such as a deep convolutional neural network to extract semantic cues regarding objects detected in the images. The object tracking can be utilized, for example, to facilitate autonomous navigation by the UAV or to generate and display augmentative information regarding tracked objects to users.

Abstract: An autonomous vehicle that is equipped with image capture devices can use information gathered from the image capture devices to plan a future three-dimensional (3D) trajectory through a physical environment. To this end, a technique is described for image-space based motion planning. In an embodiment, a planned 3D trajectory is projected into an image-space of an image captured by the autonomous vehicle. The planned 3D trajectory is then optimized according to a cost function derived from information (e.g., depth estimates) in the captured image. The cost function associates higher cost values with identified regions of the captured image that are associated with areas of the physical environment into which travel is risky or otherwise undesirable. The autonomous vehicle is thereby encouraged to avoid these areas while satisfying other motion planning objectives.

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage media for unmanned aerial vehicle visual line of sight flight operations. A UAV computer system may be configured to ensure the UAV is operating in visual line of sight of one or more ground operators. The UAV may confirm that it has a visual line of sight with the one or more user devices, such as a ground control station, or the UAV may ensure that the UAV does not fly behind or below a structure such that the ground operator would not be able to visually spot the UAV. The UAV computer system may be configured in such a way that UAV operation will maintain the UAV in visual line of sight of a base location.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for reserving airspace for UAV operations. In some implementations, a flight planning system can reserve and allocate airspace for unmanned aerial vehicle (UAV) operations. For example, a UAV operator device can submit a flight plan to the flight planning system. The flight planning system can submit a flight authorization request to an airspace management system to reserve airspace necessary for the flight plan. The flight planning system can receive approval and/or a reservation of the airspace for the flight plan from the airspace management system, generate a flight data package, and send the flight data package to the operator's device.

Abstract: Methods, systems and apparatus, for an unmanned aerial vehicle electromagnetic avoidance and utilization system. One of the methods includes obtaining a flight package indicating a flight pattern associated with inspecting a structure, the flight pattern causing the UAV to remain at a standoff distance from the structure, wherein the standoff distance is based on an electromagnetic field associated with the structure, and wherein the flight pattern is laterally constrained according to a property geofence associated with a right of way of the structure. The UAV is navigated according to the flight pattern, and the UAV captures images of the structure. For an initial portion of the flight pattern, the UAV navigates at an altitude based on the standoff distance and the property geofence towards the structure. The UAV determines a location at which to capture images of the structure, and the UAV provides the captured images to a user device.

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage media for determining asset efficiency. Unmanned Aerial Vehicles (UAVs) may be used to obtain aerial images of locations, property or structures. The aerial images may be geo-rectified, and a ortho-mosaic, digital surface model, or a point cloud may be created. In the context of an operation where mobile assets are used, such as construction or earth moving equipment, location-based event information may be obtained. The location-based event information may be used to determine road segment conditions or road topology where problematic road conditions likely exist.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may access a scan plan that includes a sequence of poses for the UAV to assume to capture images of a scan target using one or more image sensors. The UAV may check a next pose of the scan plan for obstructions. Responsive to detection of an obstruction, the UAV may determine a backup pose based at least on a field of view of the next pose. The UAV may control a propulsion mechanism to cause the UAV to fly to assume the backup pose. The UAV may capture, based on the backup pose and using the one or more image sensors, one or more images of the scan target.

Abstract: A technique is described for developing and using applications and skills with an autonomous vehicle. In an example embodiment, a development platform is provided that enables access to a developer console for developing software modules for use with an autonomous vehicle. Using the developer console, a developer user can specify instructions for causing an autonomous vehicle to perform one or more operations. For example, to control the behavior of an autonomous vehicle, the instructions can cause an executing computer system at the autonomous vehicle to generate calls to an application programming interface (API) associated with an autonomous navigation system of autonomous vehicle. Such calls to the API can be configured to adjust a parameter of a behavioral objective associated with a trajectory generation process performed by the autonomous navigation system that controls the behavior of the autonomous vehicle.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may identify a scan target. The UAV may navigate to two or more positions in relation to the scan target. The UAV may capture, using one or more image sensors of the UAV, two or more images of the scan target from different respective positions in relation to the scan target. For instance, the two or more respective positions may be selected by controlling a spacing between the two or more respective positions to enable determination of parallax disparity between a first image captured at a first position and a second image captured at a second position of the two or more positions. The UAV may determine a three-dimensional model corresponding to the scan target based in part on the determined parallax disparity of the two or more images including the first image and the second image.

Abstract: In some implementations, a UAV flight system can dynamically adjust UAV flight operations based on thermal sensor data. For example, the flight system can determine an initial flight plan for inspecting a flare stack and configure a UAV to perform an aerial inspection of the flare stack. Once airborne, the UAV can collect thermal sensor data and the flight system can automatically adjust the flight plan to avoid thermal damage to the UAV based on the thermal sensor data.

Abstract: In some examples, a device may receive, from a first camera, a plurality of images of an airspace corresponding to an area of operation of an unmanned aerial vehicle (UAV). The device may detect, based on the plurality of images from the first camera, a candidate object approaching or within the airspace. Based on detecting the candidate object, the device may control a second camera to direct a field of view of the second camera toward the candidate object. Further, based on images from the second camera captured at a first location and images from at least one other camera captured at a second location, the candidate object may be determined to be an object of interest. In addition, at least one action may be taken based on determining that the candidate object is the object of interest.

Abstract: Embodiments are described for a stabilization system configured, in some embodiments, for stabilizing image capture from an aerial vehicle (e.g., a UAV). According to some embodiments, the stabilization systems employs both active and passive stabilization means. A passive stabilization assembly includes a counter-balanced suspension system that includes an elongated arm that extends into and is coupled to the body of a vehicle. The counter-balanced suspension system passively stabilizes a mounted device such as an image capture device to counter motion of the UAV while in use. In some embodiment the counter-balanced suspension system passively stabilizes a mounted image capture assembly that includes active stabilization means (e.g., a motorized gimbal and/or electronic image stabilization). In some embodiments, the active and passive stabilization means operate together to effectively stabilize a mounted image capture device to counter a wide range of motion characteristics.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for an unmanned aerial system inspection system. One of the methods is performed by a UAV and includes obtaining, from a user device, flight operation information describing an inspection of a vertical structure to be performed, the flight operation information including locations of one or more safe locations for vertical inspection. A location of the UAV is determined to correspond to a first safe location for vertical inspection. A first inspection of the structure is performed is performed at the first safe location, the first inspection including activating cameras. A second safe location is traveled to, and a second inspection of the structure is performed. Information associated with the inspection is provided to the user device.

Abstract: Methods and systems are disclosed for an unmanned aerial vehicle (UAV) configured to autonomously navigate a physical environment while capturing images of the physical environment. In some embodiments, the motion of the UAV and a subject in the physical environment may be estimated based in part on images of the physical environment captured by the UAV. In response to estimating the motions, image capture by the UAV may be dynamically adjusted to satisfy a specified criterion related to a quality of the image capture.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a distributed system architecture for unmanned air vehicles. One of the methods includes obtaining information identifying flight information of a UAV, with the flight information including flight phase information or a contingency condition associated with a flight critical module included in the UAV. The obtained information is analyzed, and one or more first payload modules are determined to enter a modified power state. Requests to enter the modified power state are caused to be transmitted to each determined payload module in the one or more first payload modules.