A computer system obtains a raster cell of terrain data from a database, a query shape corresponding to a planned flight segment of a UAV that intersects with the raster cell, and a range of acceptable terrain elevation values for the planned flight segment. The raster cell comprises a minimum terrain elevation value, a maximum terrain elevation value, and links to sub-cells of the raster cell. The computer system determines whether the minimum and maximum terrain elevation values of the raster cell are within the range of acceptable terrain elevation values for the planned flight segment and validates the planned flight segment with respect to the raster cell based at least in part on whether the minimum and maximum terrain elevation values of the raster cell are within the range of acceptable terrain elevation values for the planned flight segment.

A computer system obtains a raster cell of terrain data from a database, a query shape corresponding to a planned flight segment of a UAV that intersects with the raster cell, and a range of acceptable terrain elevation values for the planned flight segment. The raster cell comprises a minimum terrain elevation value, a maximum terrain elevation value, and links to sub-cells of the raster cell. The computer system determines whether the minimum and maximum terrain elevation values of the raster cell are within the range of acceptable terrain elevation values for the planned flight segment and validates the planned flight segment with respect to the raster cell based at least in part on whether the minimum and maximum terrain elevation values of the raster cell are within the range of acceptable terrain elevation values for the planned flight segment.

A system (100) for planning a flight path for a survey of a ROI comprises at least one UAV (102). a flight control unit (104) and a flight planning unit (106). Flight planning unit (106) creates a main flight path (302) covering the ROI, identifies an area of interest based on trigger data within the ROI, creates a boundary (304) around the identified area of interest, and creates an additional flight path (306), which is contiguous to the main flight path (302), for the identified area of interest. The trigger data may be captured during the main flight path using sensors mounted on the UAV and the flight path planned/generated in real-time during the flight, or may be fed by user. The main flight path (302) and the additional flight path (306) are any of a back-and-forth linear paths or spiral path flight paths.

A system (100) for planning a flight path for a survey of a ROI comprises at least one UAV (102). a flight control unit (104) and a flight planning unit (106). Flight planning unit (106) creates a main flight path (302) covering the ROI, identifies an area of interest based on trigger data within the ROI, creates a boundary (304) around the identified area of interest, and creates an additional flight path (306), which is contiguous to the main flight path (302), for the identified area of interest. The trigger data may be captured during the main flight path using sensors mounted on the UAV and the flight path planned/generated in real-time during the flight, or may be fed by user. The main flight path (302) and the additional flight path (306) are any of a back-and-forth linear paths or spiral path flight paths.

Systems and methods for a helideck approach path tool. One example system includes an electronic processor. The electronic processor is configured to determine a helideck identifier and retrieve, from a database storing data on a plurality of helidecks, helideck data corresponding to the helideck identifier. The helideck data includes a helideck azimuth and at least one obstacle characteristic. The electronic processor is configured to generate a graphical user interface including a helideck approach indicator object, which includes a compass ring, a graphical representation of the helideck aligned to the compass ring based on the helideck azimuth, and an obstacle indicator overlaid on the compass ring based on the at least one obstacle characteristic. The electronic processor is configured to present the graphical user interface on a display within the aircraft.

Systems and methods for a helideck approach path tool. One example system includes an electronic processor. The electronic processor is configured to determine a helideck identifier and retrieve, from a database storing data on a plurality of helidecks, helideck data corresponding to the helideck identifier. The helideck data includes a helideck azimuth and at least one obstacle characteristic. The electronic processor is configured to generate a graphical user interface including a helideck approach indicator object, which includes a compass ring, a graphical representation of the helideck aligned to the compass ring based on the helideck azimuth, and an obstacle indicator overlaid on the compass ring based on the at least one obstacle characteristic. The electronic processor is configured to present the graphical user interface on a display within the aircraft.

A method for controlling a plurality of drones to survey a location, the method comprising, at a computing system: automatically generating preliminary flight plans for a plurality of drones to survey the location based on a 3D model; receiving survey data from the plurality of drones as the plurality of drones are surveying the location based on the preliminary flight plans; updating the 3D model based on the survey data received from the plurality of drones; and automatically updating at least a portion of the flight plans based on the updated 3D model.

A method for controlling a plurality of drones to survey a location, the method comprising, at a computing system: automatically generating preliminary flight plans for a plurality of drones to survey the location based on a 3D model; receiving survey data from the plurality of drones as the plurality of drones are surveying the location based on the preliminary flight plans; updating the 3D model based on the survey data received from the plurality of drones; and automatically updating at least a portion of the flight plans based on the updated 3D model.

This disclosure describes a method of controlling an unmanned aerial vehicle (UAV). The steps of controlling include acquiring images with an image capture device of an unmanned aerial vehicle (UAV). The steps include analyzing the images to determine navigation information of the UAV with a vision-based navigation system. The steps include tracking a position of the UAV with the vision-based navigation system. The steps include controlling rotors of the UAV to prevent deviations in movement from a desired flight path or position of the UAV. The steps include limiting travel or flight of the UAV to a physical region determined by the desired flight path.

A system for voice recognition in autonomous flight of an electric aircraft that includes a computing device communicatively connected to the electric aircraft configured to receive at least a voice datum from a remote device, wherein the voice datum is configured to include at least an expression datum, generate, using a first machine-learning process, a transcription datum as a function of the at least a voice datum, extract at least a query as a function of the transcription datum, generate, using a second machine-learning process, a communication output as a function of the at least a query, and adjust a flight plan as a function of the communication output.