Described are various embodiments of a flight management method and system using same. In one embodiment, a digital flight management system comprises: a digital processing environment comprising instructions to access: flight request data related to a flight plan; aircraft parameter data; a flight risk data source; and geographical data. The instructions are executable to: calculate a predicted flight path; digitally compare the predicted flight path with flight risk data from the flight risk data source to assess a flight risk associated with the predicted flight path; and display via a user interface the predicted fight path in accordance with the flight risk.

Ray-tracing for terrain mapping is provided. A system of an aerial vehicle can identify points generated from data captured by a sensor of the aerial vehicle. The points can each indicate a respective altitude value of a portion of terrain. The system can determine, based on the altitude values of the points, a threshold altitude of the terrain, and can identify a boundary defined in part based on the threshold altitude of the terrain. The system can generate a terrain map for the terrain based on applying a ray-tracing process to the points. The ray-tracing process can be performed within the boundary, using the points as respective sources and the aerial vehicle as a destination. The system can present a graphical representation of the terrain map in a graphical user interface of the aerial vehicle.

A response system may be provided. The response system may include an autonomous drone. The autonomous drone may include a processor, a memory in communication with the processor, and a sensor. The processor may be programmed to build a virtual map of a coverage area, store the virtual map in the memory, receive a deployment signal, deploy the drone in response to the deployment signal, control movement of the drone within the coverage area using the virtual map, collect sensor data of the coverage area using the sensor, and/or analyze the sensor data to generate an inventory list of the coverage area, the inventory list including a personal article within the coverage area.

Techniques for generating flight operation recommendation for an aircraft are described. In operation, a flight safety hazard is detected on a flight path corresponding to a current flight operation of an aircraft. In response, the current flight operation is modified to generate a modified flight operation. A plurality of avionics parameters is then obtained from avionics systems available onboard the aircraft. A variation in the flight safety hazard is then detected based on at least one avionics parameter from the plurality of avionics parameters. Upon ascertaining the variation to be detrimental to the modified flight operation of the aircraft, the plurality of avionics parameters is analysed using a flight operation recommendation model to generate a plurality of flight operation recommendations. A flight operation recommendation from the plurality of flight operation recommendations is then applied to the modified flight operation.

Systems, devices, and methods for determining, by a processor, an unmanned aerial system (UAS) position relative to at least one flight boundary; and effecting, by the processor, at least one flight limitation of a UAS if the determined UAS position crosses the at least one flight boundary.

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.

The present disclosure provides a control system for controlling unmanned autonomous systems (UAS). The control system comprises of an application user system 102 to operate the UAS, an operating system 103, a virtual road system (VRS) 109 and a virtual packet 501. The virtual packet 501 created as a boundary around the UAS defined by application user system 102 or VRS 109. The operating system 103 includes a machine learning processing unit (MLPU) 104 configured for positioning the UAS, detecting collision within path of the virtual packet 901. The VRS 109 configured to generate a virtual roadway 902 using architecture for routing the UAS. The routing and controlling of UAS by the VRS 109 is based on request received from the MLPU 104, application zone packet parameters and actual position co-ordinates received from the MLPU 104.

Systems, methods, and devices are provided for generating flight restriction zones associated with flight response measures. The flight restriction zones may be generated with one or more flight restriction strips. Flight response measures for an unmanned aerial vehicle (UAV) may be directed based on a location and/or movement characteristic of the UAV relative to the one or more flight restriction strips. Different flight-response measures may be taken based on various parameters.

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.