System and method for pilot assistance in an electric aircraft
A system and method for pilot assistance in an electric vertical takeoff and landing (eVTOL) aircraft. The system generally includes a pilot control and a flight controller. The pilot control is attached to the eVTOL aircraft. The pilot control is configured to transmit an input relating to the flight path of the aircraft. The flight controller is communicatively connected to the pilot control. The flight controller is configured to receive the input relating to the flight path, generate an output of a recommended flight maneuver as a function of the input, and display the recommended flight maneuver.
1. A system for pilot assistance in an electric aircraft, the system comprising:
a pilot control attached to an electric aircraft; and
a flight controller communicatively connected to the pilot control, wherein the flight controller is configured to:
receive an input from the pilot control;
generate an output of a recommended maneuver as a function of the input;
transmit the output of the recommended maneuver to a remote device; and
control an electric propulsor of the electric aircraft as a function of the output of the recommended maneuver, wherein the electric propulsor is configured to propel the electric aircraft.
2. The system of claim 1 , wherein the pilot control is operated by a voice command.
3. The system of claim 1 , wherein the remote device is configured to display the output of the recommended maneuver to a user of the electric aircraft.
4. The system of claim 1 , wherein the electric aircraft comprises a drone.
5. The system of claim 1 , wherein the flight controller is further configured to identify a geographic location datum.
6. The system of claim 5 , wherein the flight controller is further configured to generate the output of the recommended maneuver as a function of the input and the geographic location datum.
7. The system of claim 1 , wherein generating the output of the recommended maneuver further comprises:
selecting a training set as a function of the input and the electric aircraft, wherein the input is correlated to an element of maneuver data; and
generating, using a machine-learning model, an output based on the input and the selected training set.
8. The system of claim 7 , wherein the machine-learning model includes a neural network machine-learning model.
9. The system of claim 1 , wherein the pilot control is configured to receive the input from a user.
10. The system of claim 1 , wherein the pilot control comprises a simulator device.
11. A method for pilot assist of an electric aircraft, the method comprising:
receiving, at a flight controller, an input from a pilot control of an electric aircraft that is communicatively connected to the flight controller;
generating, at the flight controller, an output of a recommended maneuver as a function of the input;
transmitting, at the flight controller, the output of the recommended maneuver to a remote device; and
controlling, at the flight controller, a propulsor of the electric aircraft as a function of the output of the recommended maneuver.
12. The method of claim 11 , wherein the pilot control is operated by a voice command.
13. The method of claim 11 , wherein the remote device is configured to display the output of the recommended maneuver to a user of the electric aircraft.
14. The method of claim 11 , wherein the electric aircraft comprises a drone.
15. The method of claim 11 , further comprising identifying, at the flight controller, a geographic location datum.
16. The method of claim 15 , further comprising generating, at the flight controller, the output of the recommended maneuver as a function of the input and the geographic location datum.
17. The method of claim 11 , wherein generating the output further comprises:
selecting a training set as a function of the input and the electric aircraft, wherein the input is correlated to an element of maneuver data; and
generating, using a machine-learning model, an output based on the input and the selected training set.
18. The method of claim 17 , wherein the machine-learning model includes a neural network machine-learning model.
19. The method of claim 11 , further comprising receiving, at the pilot control, the input from a user.
20. The method of claim 11 , wherein the pilot control comprises a simulator device.