An aerial vehicle is provided. The aerial vehicle can include a plurality of sensors mounted thereon, an avionics system configured to operate at least a portion of the aerial vehicle, and a machine vision controller in operative communication with the avionics system and the plurality of sensors. The machine vision controller is configured to perform a method. The method includes obtaining sensor data from at least one sensor of the plurality of sensors, determining performance data from the avionic system or an additional sensor of the plurality of sensors, processing the sensor data based on the performance data to compensate for movement of the unmanned aerial vehicle, identifying at least one geographic indicator based on processing the sensor data, and determining a geographic location of the aerial vehicle based on the at least one geographic indicator.

Boundary information associated with a three-dimensional (3D) flying space is obtained, including a boundary of the 3D flying space. Location information associated with an aircraft is obtained, including a location of the aircraft. Information is presented based at least in part on the boundary information associated with the 3D flying space and the location information associated with the aircraft, including by presenting feedback in proportion to the distance between the boundary of the flying space and the location of the aircraft. An intensity of the feedback increases in proportion to decreasing distance between the boundary of the flying space and the location of the aircraft.

A registration authority (RA) server registers unmanned aerial vehicles (UAVs) and their owners/operators (O/O). A UAV is maintained in a flight lock state until a flight plan request from the O/O is approved by the RA, which sends an key-signed approval to unlock the UAV's flight lock. The RA server evaluates a UAV's proposed flight plan based on the attributes of the O/O and UAV, the location and time of the requested flight plan, and a set of flight rules and exclusion zones that are developed in view of privacy assurance, security assurance, flight safety assurance, and ground safety assurance. The flight plan key-signed approval supplied to the UAV by the RA server specifies an inclusion zone that corresponds to a flight plan trajectory to be followed. Once in flight, the UAV maintains real-time knowledge of its position and time to ensure its flight remains within the approved inclusion zone.

Systems and methods are disclosed for generating a digital flight path within complex mission boundaries. In particular, in one or more embodiments, systems and methods generate flight legs that traverse a target site within mission boundaries. Moreover, one or more embodiments include systems and methods that utilize linking algorithms to connect the generated flight legs into a flight path. Moreover, one or more embodiments include systems and methods that generate a mission plan based on the flight path. In one or more embodiments, the generated mission plan enables a UAV to traverse a flight area within mission boundaries and capture aerial images with regard to the target site.

An emergency unmanned aerial vehicle (UAV) and a method for employing a UAV. The method includes storing a digital elevation model (DEM) and associated data including locations of communication networks, updating the locations of communication networks in the associated data via a wireless transceiver, and storing position information determined by a global navigation satellite system (GNSS) receiver. The method includes detecting a predetermined condition using electronic sensors, determining whether the UAV is within a communications range of any communication network via the wireless transceiver, and determining a path to a communication network using the DEM and the associated data. The method also includes causing the UAV to become airborne and fly along the path, and transmitting a distress message via the wireless transceiver to the communication network, the distress message including position information corresponding to a location where the UAV detected the predetermined condition.

A system and method for management of airspace for unmanned aircraft is disclosed. The system and method comprises administration of the airspace including designation of flyways and zones with reference to features in the region. The system and method comprises administration of aircraft including registration of aircraft and mission. A monitoring system tracks conditions and aircraft traffic in the airspace. Aircraft may be configured to transact with the management system including to obtain rights/priority by license and to operate in the airspace under direction of the system. The system and aircraft may be configured for dynamic transactions (e.g. licensing/routing). The system will set rates for licenses and use/access to the airspace and aircraft will be billed/pay for use/access of the airspace at rates using data from data sources.

Systems and methods for UAV safety are provided. An authentication system may be used to confirm UAV and/or user identity and provide secured communications between users and UAVs. The UAVs may operate in accordance with a set of flight regulations. The set of flight regulations may be associated with a geo-fencing device in the vicinity of the UAV.

Systems and methods for UAV safety are provided. An authentication system may be used to confirm UAV and/or user identity and provide secured communications between users and UAVs. The UAVs may operate in accordance with a set of flight regulations. The set of flight regulations may be associated with a geo-fencing device in the vicinity of the UAV.

Systems and methods for UAV safety are provided. An authentication system may be used to confirm UAV and/or user identity and provide secured communications between users and UAVs. The UAVs may operate in accordance with a set of flight regulations. The set of flight regulations may be associated with a geo-fencing device in the vicinity of the UAV.

Within examples, systems and methods of generating a synthetic image representative of an environment of a vehicle are described comprising generating a first image using infrared information from an infrared (IR) camera, generating a second image using laser point cloud data from a LIDAR, generating an embedded point cloud representative of the environment based on a combination of the first image and the second image, receiving navigation information traversed by the vehicle, transforming the embedded point cloud into a geo-referenced coordinate space based on the navigation information, and combining the transformed embedded point cloud with imagery of terrain of the environment to generate the synthetic image representative of the environment of the vehicle.