IP Library › Granted Patent US 12,462,612
Granted Patent B2
US 12,462,612 · App. 18/392,724 · Granted Nov 4, 2025

Systems and methods for remotely controlling locomotives with gestures

Inventors: Jeremy Jovenall (Mercer, PA); Brian Fette (Canfield, OH); Ryan Wooten (Strongsville, OH); Ronald Timothy Bailey, Jr. (Newton Falls, OH)
Assignee: Cattron North America, Inc.
G06V40/28B61L3/065G06F3/017G06V10/82G06V20/56G06V40/10
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 12,462,612
App. No.
18/392,724
Granted
Nov 4, 2025
Kind
B2
Abstract

Exemplary embodiments are disclosed of systems and methods for remotely controlling locomotives with gestures. In an exemplary embodiment, a system is configured for allowing an operator(s) to remotely control operation of a locomotive with gesture(s) made by an operator(s). The system includes at least one processor configured to be operable for visually recognizing gesture(s) made by an operator(s) in one or more images captured by at least one camera. A locomotive control unit is configured to be operable for controlling the operation of the locomotive according to the visually recognized gesture(s) made by the operator(s).

Claims (55)

1 . A system comprising a locomotive control unit configured to be operable for controlling operation of a locomotive according to a gesture(s) made by an operator(s) and visually recognized, via at least one processor, in one or more images captured by at least one camera, wherein:

the at least one camera, the at least one processor, and the locomotive control unit are onboard the locomotive thereby providing an onboard system configuration for gesture-based control that is fully contained onboard the locomotive; and/or

the system is configured for allowing the operator(s) to remotely control operation of the locomotive with gesture(s) made by the operator(s) including starting, stopping, accelerating, and decelerating.

2 . The system of claim 1 , wherein the at least one processor is in communication with the locomotive control unit via a communication link.

3 . The system of claim 1 , wherein the at least one processor comprises an edge processing device and/or a neural network.

4 . The system of claim 1 , wherein the at least one processor comprises an edge processing device running a single shot detector (SSD) neural network.

5 . The system of claim 1 , wherein:

the at least one processor is in communication via a serial connection with the locomotive control unit;

the at least one processor is configured to be operable for relaying one or more decisions, commands, and/or instructions to the locomotive control unit over the serial connection based on the visually recognized gesture(s); and

the locomotive control unit is configured to be operable for controlling operation of the locomotive according to the one or more decisions, commands, and/or instructions relayed to the locomotive control unit from the at least one processor over the serial connection.

6 . The system of claim 1 , wherein the locomotive control unit is configured to be operable for controlling operation of the locomotive in accordance with an algorithm(s) associated with or allocated to the visually recognized gesture(s).

7 . The system of claim 1 , wherein:

the system includes the at least one camera comprising at least one video camera onboard the locomotive for capturing video of the gesture(s) made by the operator(s); and

the locomotive control unit is configured to be operable for controlling operation of the locomotive according to the gesture(s) made by the operator(s) and visually recognized, via the at least one processor, in the video captured by the at least one video camera.

8 . The system of claim 1 , wherein:

the system includes the at least one camera comprising at least one video camera onboard the locomotive for capturing video of the gesture(s) made by the operator(s);

the locomotive control unit integrally includes the at least one processor; and

the at least one processor integrally included within the locomotive control unit is configured to be operable for analyzing a video feed of the operator(s) captured by the at least one video camera and visually recognizing the gesture(s) made by the operator(s) in the video feed captured by the at least one video camera.

9 . The system of claim 1 , wherein the at least one processor is configured to be operable for visually recognizing gesture(s) made by the operator(s) including one or more of an operator's hand signal(s), body language, and/or pose(s).

10 . The system of claim 1 , wherein:

the locomotive control unit integrally includes the at least one processor that is operable for visually recognizing the gesture(s) made by the operator(s) in the one or more images captured by the at least one camera, whereby the system is configured for allowing the operator(s) to remotely control operation of the locomotive with gesture(s) made by the operator(s) including starting, stopping, accelerating, decelerating, light(s), and audible alert(s); and

an entirety of the system including the at least one camera, the locomotive control unit, and the at least one processor integrally included within the locomotive control unit are onboard the locomotive thereby providing an onboard system configuration for gesture-based control that is fully contained onboard the locomotive.

11 . The system of claim 10 , wherein the at least one processor integrally included within the locomotive control unit comprises an edge processing device and/or a neural network.

12 . The system of claim 10 , wherein the at least one processor integrally included within the locomotive unit comprises an edge processing device running a single shot detector (SSD) neural network.

13 . The system of claim 10 , wherein the at least one processor integrally included within the locomotive unit includes artificial intelligence operable for visually recognizing the gesture(s) made by the operator(s) in the one or more images captured by the at least one camera.

14 . A method comprising controlling operation of a locomotive, via a locomotive control unit, according to a gesture(s) made by an operator(s) and visually recognized, via at least one processor, in one or more images captured by at least one camera, wherein:

the at least one camera, the at least one processor, and the locomotive control unit are onboard the locomotive thereby providing an onboard system configuration for gesture-based control that is fully contained onboard the locomotive; and/or

the system is configured for allowing the operator(s) to remotely control operation of the locomotive with gesture(s) made by the operator(s) including starting, stopping, accelerating, and decelerating.

15 . The method of claim 14 , wherein:

the at least one processor is in communication via a serial connection with the locomotive control unit;

the method includes

relaying one or more decisions, commands, and/or instructions based on the visually recognized gesture(s) from the at least one processor over the serial connection to the locomotive control unit; and

controlling operation of the locomotive, via the locomotive control unit, according to the one or more decisions, commands, and/or instructions relayed to the locomotive control unit from the at least one processor over the serial connection.

16 . The method of claim 14 , wherein the method includes controlling operation of the locomotive, via the locomotive control unit, in accordance with an algorithm(s) associated with or allocated to the visually recognized gesture(s).

17 . The method of claim 14 , wherein:

the at least one camera comprises at least one video camera onboard the locomotive for capturing video of the gesture(s) made by the operator(s);

the locomotive control unit integrally includes the at least one processor; and

the method includes:

capturing, via the at least one video camera, video of the gesture(s) made by the operator(s); and

visually recognizing, via the at least one processor of the locomotive control unit, the gesture(s) made by the operator(s) in the video captured by the at least one video camera.

18 . The method of claim 14 , wherein the visually recognized gesture(s) made by the operator(s) comprise one or more of an operator's hand signal(s), body language, and/or pose(s).

19 . The method of claim 14 , wherein:

the locomotive control unit integrally includes at least one processor operable for visually recognizing the gesture(s) made by the operator(s) in the one or more images captured by the at least one camera, whereby the system is configured for allowing the operator(s) to remotely control operation of the locomotive with gesture(s) made by the operator(s) including starting, stopping, accelerating, decelerating, light(s), and audible alert(s); and

the at least one camera, the locomotive control unit, the at least one processor integrally included within the locomotive control unit are onboard the locomotive thereby providing an onboard system configuration for gesture-based control that is fully contained onboard the locomotive.

20 . A system for remotely controlling operation of a locomotive with a gesture(s) made by an operator(s), the system comprising a locomotive control unit configured to be operable for controlling operation of the locomotive according to a gesture(s) made by an operator(s) and visually recognized in one or more images captured by at least one camera, wherein:

the at least one camera and the locomotive control unit are onboard the locomotive thereby providing an onboard system configuration for gesture-based control that is fully contained onboard the locomotive; and/or

the system is configured for allowing the operator(s) to remotely control operation of the locomotive with gesture(s) made by the operator(s) including starting, stopping, accelerating, and decelerating.

21 . The system of claim 20 , wherein:

the system includes the at least one camera comprising at least one video camera onboard the locomotive for capturing video of the gesture(s) made by the operator(s); and

the locomotive control unit integrally includes at least one processor configured to be operable for analyzing a video feed of the operator(s) captured by the at least one video camera and visually recognizing the gesture(s) made by the operator(s) in the video feed captured by the at least one video camera.

22 . The system of claim 20 , wherein:

the system is configured for allowing the operator(s) to remotely control operation of the locomotive with gesture(s) made by the operator(s) including starting, stopping, accelerating, decelerating, light(s), and audible alert(s); and

an entirety of the system including the at least one camera, the locomotive control unit, and the at least one processor integrally included within the locomotive control unit are onboard the locomotive thereby providing the onboard system configuration for gesture-based control that is fully contained onboard the locomotive.

23 . The system of claim 22 , wherein the locomotive control unit integrally includes at least one processor operable for visually recognizing the gesture(s) made by the operator(s) in the one or more images captured by the at least one camera.

24 . The system of claim 22 , wherein the system includes an edge processing device running a single shot detector (SSD) neural network that is operable for visually recognizing the gesture(s) made by the operator(s) in the one or more images captured by the at least one camera.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 10, 2024
From: JOVENALL, JEREMY; FETTE, BRIAN; BAILEY, RONALD TIMOTHY, JR.; WOOTEN, RYAN
To: CATTRON NORTH AMERICA, INC.
Reel/Frame 066081/0292 →
Continuity (3)
Continuation 17959159 · Oct 3, 2022
Provisional Application 63273893 · Oct 30, 2021
Related Publication 20240135752A1 · Apr 25, 2024
References Cited (40)
US 5021715A · Smith et al. · 1991 [cited by applicant]
US 6693584B2 · Horst · 2004 [cited by applicant]
US 6697716B2 · Horst · 2004 [cited by applicant]
US 6789004B2 · Brousseau · 2004 [cited by applicant]
US 6863247B2 · Horst · 2005 [cited by applicant]
US 6928342B2 · Horst · 2005 [cited by applicant]
US RE39011E · Horst · 2006 [cited by applicant]
US RE39210E · Horst · 2006 [cited by applicant]
US 7236859B2 · Horst · 2007 [cited by applicant]
US 7379572B2 · Yoshida et al. · 2008 [cited by applicant]
US 8170372B2 · Kennedy et al. · 2012 [cited by applicant]
US 8971581B2 · Wu et al. · 2015 [cited by applicant]
US 10186147B2 · Imai · 2019 [cited by applicant]
US 11854309B2 · Jovenall · 2023 [cited by applicant]
US 20040117073A1 · Horst · 2004 [cited by applicant]
US 20040129840A1 · Horst · 2004 [cited by applicant]
US 20160170494A1 · Bonnet · 2016 [cited by applicant]
US 20180034950A1 · Tanabe et al. · 2018 [cited by applicant]
US 20190156475A1 · Markson et al. · 2019 [cited by applicant]
US 20200379575A1 · Banerjee et al. · 2020 [cited by applicant]
US 20210201661A1 · Al Jazaery · 2021 [cited by examiner]
US 20220092862A1 · Faulkner · 2022 [cited by examiner]
US 20220366698A1 · Braun · 2022 [cited by applicant]
US 20230202540A1 · Ono et al. · 2023 [cited by applicant]
US 20230280835A1 · McDaniel et al. · 2023 [cited by applicant]
AU 2021104072A4 · 2021 [cited by examiner]
DE 102007021580A1 · 2008 [cited by applicant]
DE 102012203197A1 · 2013 [cited by examiner]
WO WO2006106789A1 · 2006 [cited by applicant]
Acharjya (Year: 202). [cited by examiner]
Braband (Year: 2013). [cited by examiner]
Standard Railroad Signals, By George H. Baker, 2022, 32 pages. [cited by applicant]
Systems for Edge Computing; NVIDIA, 6 pages, accessed Oct. 14, 2021. [cited by applicant]
Kumar et al., Object detection in real time based on imrpoved single shot multi-box detector algorithm,—<i>EURASIP Journal on Wireless Communications and Networking</i>; 2020, 18 pages. [cited by applicant]
OCU-III for Rail, BELTPACK™, Cattron.com, Jun. 2021, 2 pages. [cited by applicant]
LCS-III Locomotive Control System, Cattron.com, accessed Oct. 14, 2021, 2 pages. [cited by applicant]
Beltpack™ Locomotive Remote Control System, Cattron.com, accessed Oct. 1, 2021, 2 pages. [cited by applicant]
Safety Posters; Standard Crane Hand Signals, accuform.com, Sep. 21, 2021, 4 pages. [cited by applicant]
Boom Crane Hand Signals, accessed Sep. 21, 2021, 1 pages. [cited by applicant]
Rule 12. Hand, Flag and Lamp Signals, Streamlined Backshop Services, 2010-2022; 7 pages. [cited by applicant]