IP Library Granted Patent US 12,372,957
Granted Patent B2
US 12,372,957 · App. 18/200,284 · Granted Jul 29, 2025

Systems and methods for the remote piloting of an electric aircraft

Inventors: Nicholas Moy (South Burlington, VT); Collin Freiheit (Burlington, VT); Joshua E. Auerbach (Waterbury Center, VT)
Assignee: BETA AIR LLC
G05D1/0011B64C39/024G05D1/102
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,372,957
App. No.
18/200,284
Granted
Jul 29, 2025
Kind
B2
Abstract

A system and method for the remote piloting of an electric aircraft is illustrated. The system comprises a remote device located outside an electric aircraft, wherein the remote device is configured to receive a flight command input from a user and transmit the flight command input to a flight controller located on the aircraft. The flight controller is located inside the aircraft and configured to receive the flight command input from the remote device and enact the flight command autonomously as a function of the flight command input.

Claims (43)

1. A system for remote piloting of an aircraft, the system comprising:

a remote device located outside and communicatively connected to the aircraft, wherein:

the remote device comprises a pilot input configured to receive a flight command input from a user; and

the remote device is configured to:

transmit the flight command input to a flight controller located on the aircraft, wherein flight command input configures the flight controller to enact a flight command autonomously based on the flight command input, and wherein enacting the flight command autonomously based on the flight command input comprises:

providing input data determined based on the flight command input to a machine learning model,

receiving the flight command from the machine learning model, and

controlling the aircraft based on the flight command; and

receive sensor input from the flight controller.

2. The system of claim 1 , wherein the sensor input comprises flight component specific data.

3. The system of claim 2 , wherein the remote device comprises a display configured to display, to the user, the flight component specific data.

4. The system of claim 2 , wherein enacting the flight command comprises applying the flight command input to a flight component.

5. The system of claim 1 , wherein enacting the flight command comprises:

changing from a first method of flying the aircraft to a second method of flying the aircraft, wherein:

the first method of flying the aircraft comprises a rotor-based flight; and the second method of flying the aircraft comprises a fixed wing flight.

6. The system of claim 1 , wherein the flight command input comprises an altitude adjustment.

7. The system of claim 6 , wherein enacting the flight command comprises:

adjusting an altitude of the aircraft based on the altitude adjustment.

8. The system of claim 1 , wherein the flight controller is further configured to identify a location of the aircraft.

9. The system of claim 1 , wherein the flight controller is further configured to generate the flight command based on the flight command input before enacting it.

10. The system of claim 1 , wherein the remote device is further configured to:

generate a simulation of the aircraft based on the flight command input, wherein generating the simulation of the aircraft comprises:

generating an aircraft model, wherein the aircraft model comprises sensor model.

11. The system of claim 1 , wherein the input data is further determined based on a state of the aircraft and data generated based on simulating an operation of the aircraft.

12. A method for remote piloting of an aircraft (eVTOL), the method comprising:

locating a remote device outside and communicatively connected to the aircraft, wherein the remote device comprises pilot input configured to receive a flight command input from a user;

transmitting, at a remote device, the flight command input to a flight controller located on the aircraft, wherein flight command input configures the flight controller to enact a flight command autonomously based on the flight command input, and wherein enacting the flight command autonomously based on the flight command input comprises:

providing input data determined based on the flight command input to a machine learning model,

receiving the flight command from the machine learning model, and

controlling the aircraft based on the flight command; and

receive, from the flight controller, sensor input.

13. The method of claim 12 , wherein the sensor input comprises flight component specific data.

14. The method of claim 13 , wherein the remote device comprises a display configured to display, to the user, the flight component specific data.

15. The method of claim 13 , wherein enacting the flight command comprises applying the flight command input to a flight component.

16. The method of claim 12 , wherein enacting the flight command comprises: changing from a first method of flying the aircraft to a second method of flying the aircraft, wherein:

the first method of flying the aircraft comprises a rotor-based flight; and

the second method of flying the aircraft comprises a fixed wing flight.

17. The method of claim 12 , wherein the flight command input comprises an altitude adjustment.

18. The method of claim 17 , wherein enacting the flight command comprises: adjusting an altitude of the aircraft based on the altitude adjustment.

19. The method of claim 12 , wherein the flight controller is further configured to generate the flight command based on the flight command input before enacting it.

20. The method of claim 12 , wherein the method further comprises:

generating, using the remote device, a simulation of the aircraft based on the flight command input, wherein generating the simulation of the aircraft comprises:

generating, using the remote device, an aircraft model, wherein the aircraft model comprises sensor model.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 8, 2024
From: MOY, NICHOLAS; FREIHEIT, COLLIN; AUERBACH, JOSHUA E.
To: BETA AIR, LLC
Reel/Frame 067346/0249 →
Continuity (2)
Continuation In Part 17732396 · Apr 28, 2022
Related Publication 20230350404A1 · Nov 2, 2023
References Cited (43)
US 5067674A · Heyche · 1991 [cited by applicant]
US 9108729B2 · Duggan · 2015 [cited by applicant]
US 9412278B1 · Gong · 2016 [cited by applicant]
US 9766622B1 · Yang · 2017 [cited by applicant]
US 10001776B2 · Rangarajan · 2018 [cited by applicant]
US 10202190B2 · Tao · 2019 [cited by applicant]
US 10953984B2 · Blake · 2021 [cited by applicant]
US 11008098B2 · Zhang · 2021 [cited by applicant]
US 11077937B1 · Bruell · 2021 [cited by applicant]
US 11084584B2 · Sloan · 2021 [cited by applicant]
US 11353890B1 · Auerbach · 2022 [cited by applicant]
US 11358730B1 · Freiheit · 2022 [cited by applicant]
US 11417224B1 · Freiheit · 2022 [cited by applicant]
US 11454990B1 · List · 2022 [cited by applicant]
US 20050004723A1 · Duggan · 2005 [cited by applicant]
US 20160031554A1 · Eshkenazy · 2016 [cited by applicant]
US 20160236790A1 · Knapp · 2016 [cited by applicant]
US 20160297520A1 · Sada-Salinas · 2016 [cited by applicant]
US 20170108866A1 · Quinn · 2017 [cited by applicant]
US 20170233071A1 · Pilskalns · 2017 [cited by applicant]
US 20170269594A1 · Sydnor · 2017 [cited by applicant]
US 20170308100A1 · Iskrev · 2017 [cited by applicant]
US 20170349280A1 · Liao · 2017 [cited by applicant]
US 20180002011A1 · Mccullough · 2018 [cited by applicant]
US 20180002012A1 · Mccullough · 2018 [cited by applicant]
US 20180002013A1 · Mccullough · 2018 [cited by applicant]
US 20180002014A1 · Mccullough · 2018 [cited by applicant]
US 20200132841A1 · Lovering · 2020 [cited by applicant]
US 20200140079A1 · Campbell · 2020 [cited by applicant]
US 20200156785A1 · Gibboney · 2020 [cited by applicant]
US 20200354049A1 · Noppel · 2020 [cited by applicant]
US 20210053670A1 · Landry · 2021 [cited by applicant]
US 20210089134A1 · Tran · 2021 [cited by applicant]
US 20210120176A1 · Wang · 2021 [cited by applicant]
US 20210183255A1 · Van Tulder · 2021 [cited by applicant]
US 20210316847A1 · Predonu · 2021 [cited by applicant]
US 20210362851A1 · Mccullough · 2021 [cited by applicant]
US 20210362857A1 · Mccullough · 2021 [cited by applicant]
US 20220147066A1 · Choi · 2022 [cited by applicant]
US 20220169366A1 · Truong · 2022 [cited by applicant]
US 20220317706A1 · Moy · 2022 [cited by applicant]
Tabassum et al., “Dynamic Control Allocation between Onboard and Delayed Remote Control for Unmanned Aircraft System Detect-and-Avoid,” arXiv:2103.07820v1, Mar. 2021, 30 pages. [cited by applicant]
Zafar et al., “Design and development of effective manual control system for unmanned air vehicle,” 3rd International Conference on Computer Research and Development, Mar. 11-13, 2011, pp. 349-353. [cited by applicant]