IP Library Granted Patent US 12,608,020
Granted Patent B2
US 12,608,020 · App. 18/630,046 · Granted Apr 21, 2026

System and method for controlling an aerial drone for exploring off-road trails

Inventor: John-Michael McNew (Ann Arbor, MI)
Assignees: Toyota Motor Engineering & Manufacturing North America, Inc.; Toyota Jidosha Kabushiki Kaisha
G05D1/639G05D2107/30
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Quick Facts
Patent No.
US 12,608,020
App. No.
18/630,046
Granted
Apr 21, 2026
Kind
B2
Abstract

A system includes a processor and a memory in communication with the processor. The memory includes instructions that cause the processor to determine, based on images of an off-road trail captured by an aerial drone in communication with a vehicle, whether the off-road trail has a positive condition indicating that the vehicle can traverse the off-road trail or an abandonment condition indicating that the vehicle cannot traverse the off-road trail. Depending on the determination, the processor either controls the aerial drone to navigate along the off-road trail or controls the aerial drone to navigate to a different off-road trail.

Claims (44)

1 . A system comprising:

a processor;

a memory in communication with the processor, the memory including an instruction module having instructions that, when executed by the processor, cause the processor to:

determine, based on images of a first off-road trail captured by an aerial drone in communication with a vehicle, whether the first off-road trail has a positive condition indicating that the vehicle can physically traverse the first off-road trail or an abandonment condition indicating that the vehicle cannot physically traverse the first off-road trail due to an encumbrance that prevents the vehicle from traversing the first off-road trail; and

control the aerial drone to navigate to a second off-road trail when the first off-road trail has the abandonment condition.

2 . The system of claim 1 , wherein the instruction module further comprises instructions that, when executed by the processor, cause the processor to control the aerial drone to navigate along the first off-road trail when the first off-road trail has the positive condition.

3 . The system of claim 1 , wherein the instruction module further comprises instructions that, when executed by the processor, cause the processor to:

request navigation instructions from an occupant of the vehicle when the first off-road trail has neither the positive condition nor the abandonment condition; and

control the aerial drone to execute the navigation instructions from the occupant.

4 . The system of claim 1 , wherein the instruction module further comprises instructions that, when executed by the processor, cause the processor to:

request navigation instructions from an occupant of the vehicle when the first off-road trail branches into a plurality of trails; and

control the aerial drone to execute the navigation instructions from the occupant to navigate along one of the plurality of trails.

5 . The system of claim 1 , wherein the positive condition further includes a feature identified by the occupant.

6 . The system of claim 1 , wherein the instruction module further comprises instructions that, when executed by the processor, cause the processor to generate a sparse map based on the images captured by the aerial drone.

7 . The system of claim 6 , wherein the sparse map is interactable by an occupant of the vehicle.

8 . The system of claim 1 , wherein the instruction module further comprises instructions that, when executed by the processor, cause the processor to:

determine a transmission range between the aerial drone and the vehicle; and

control the aerial drone to operate within the transmission range.

9 . A method comprising steps of:

determining, based on images of a first off-road trail captured by an aerial drone in communication with a vehicle, whether the first off-road trail has a positive condition indicating that the vehicle can physically traverse the first off-road trail or an abandonment condition indicating that the vehicle physically cannot traverse the first off-road trail due to an encumbrance that prevents the vehicle from traversing the first off-road trail; and

controlling the aerial drone to navigate to a second off-road trail when the first off-road trail has the abandonment condition.

10 . The method of claim 9 , further comprising the step of controlling the aerial drone to navigate along the first off-road trail when the first off-road trail has the positive condition.

11 . The method of claim 9 , further comprising the steps of:

requesting navigation instructions from an occupant of the vehicle when the first off-road trail has neither the positive condition nor the abandonment condition; and

controlling the aerial drone to execute the navigation instructions from the occupant.

12 . The method of claim 9 , further comprising the steps of:

requesting navigation instructions from an occupant of the vehicle when the first off-road trail branches into a plurality of trails; and

controlling the aerial drone to execute the navigation instructions from the occupant to navigate along one of the plurality of trails.

13 . The method of claim 9 , wherein the positive condition further includes a feature identified by the occupant.

14 . The method of claim 9 , further comprising the step of generating a sparse map based on the images captured by the aerial drone.

15 . The method of claim 14 , wherein the sparse map is interactable by an occupant of the vehicle.

16 . The method of claim 9 , further comprising the steps of:

determining a transmission range between the aerial drone and the vehicle; and

controlling the aerial drone to operate within the transmission range.

17 . A non-transitory computer-readable medium including instructions that, when executed by a processor, causes the processor to:

determine, based on images of a first off-road trail captured by an aerial drone in communication with a vehicle, whether the first off-road trail has a positive condition indicating that the vehicle can physically traverse the first off-road trail or an abandonment condition indicating that the vehicle cannot physically traverse the first off-road trail due to an encumbrance that prevents the vehicle from traversing the first off-road trail; and

control the aerial drone to navigate to a second off-road trail when the first off-road trail has the abandonment condition.

18 . The non-transitory computer-readable medium of claim 17 , further including instructions that, when executed by the processor, cause the processor to control the aerial drone to navigate along the first off-road trail when the first off-road trail has the positive condition.

19 . The non-transitory computer-readable medium of claim 17 , further including instructions that, when executed by the processor, cause the processor to:

request navigation instructions from an occupant of the vehicle when the first off-road trail has neither the positive condition nor the abandonment condition; and

control the aerial drone to execute the navigation instructions from the occupant.

20 . The non-transitory computer-readable medium of claim 17 , further including instructions that, when executed by the processor, cause the processor to:

request navigation instructions from an occupant of the vehicle when the first off-road trail branches into a plurality of trails; and

control the aerial drone to execute the navigation instructions from the occupant to navigate along one of the plurality of trails.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 22, 2026
From: TOYOTA JIDOSHA KABUSHIKI KAISHA
To: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.
Reel/Frame 074740/0573 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 11, 2024
From: MCNEW, JOHN-MICHAEL
To: TOYOTA MOTOR ENGINEERING & MANUFACTURING NORTH AMERICA, INC.; TOYOTA JIDOSHA KABUSHIKI KAISHA
Reel/Frame 067070/0839 →
Continuity (1)
Related Publication 20250315059A1 · Oct 9, 2025
References Cited (36)
US 10173776B2 · Goldberg · 2019 [cited by examiner]
US 10192182B2 · Whipple · 2019 [cited by examiner]
US 10585439B2 · Buttolo · 2020 [cited by examiner]
US 10593216B2 · Chow · 2020 [cited by examiner]
US 10642279B2 · Lockwoord et al. · 2020 [cited by applicant]
US 10936176B1 · Clark et al. · 2021 [cited by applicant]
US 10983201B2 · Pimentel et al. · 2021 [cited by applicant]
US 11074811B2 · Fowe · 2021 [cited by examiner]
US 11164149B1 · Williams · 2021 [cited by examiner]
US 11415989B2 · Bennie · 2022 [cited by examiner]
US 11453494B2 · Bouffard et al. · 2022 [cited by applicant]
US 11465740B2 · Perez Barrera · 2022 [cited by examiner]
US 11557211B2 · Chow · 2023 [cited by examiner]
US 11644839B2 · Zhao et al. · 2023 [cited by applicant]
US 11797019B2 · Parenti et al. · 2023 [cited by applicant]
US 12154443B2 · Yocam · 2024 [cited by examiner]
US 12361505B2 · Hart · 2025 [cited by examiner]
US 20180107209A1 · Hardee · 2018 [cited by examiner]
US 20190197890A1 · Du · 2019 [cited by examiner]
US 20190227555A1 · Sun et al. · 2019 [cited by applicant]
US 20190344679A1 · Miller · 2019 [cited by examiner]
US 20190348857A1 · Dudar · 2019 [cited by examiner]
US 20200398985A1 · Hsu · 2020 [cited by applicant]
US 20210165426A1 · White · 2021 [cited by examiner]
US 20210278834A1 · Kendoul et al. · 2021 [cited by applicant]
US 20210325898A1 · Golov · 2021 [cited by applicant]
US 20240255205A1 · Jervas · 2024 [cited by examiner]
CN 105185143A · 2015 [cited by applicant]
CN 110597275A · 2019 [cited by applicant]
CN 111086518B · 2022 [cited by applicant]
KR 20220166689A · 2023 [cited by applicant]
Brahmbhatt et al., Neural network approach for vision-based track navigation using low-powered computers on mavs, 2017, IEEE, p. 578-583 (Year: 2017). [cited by examiner]
Sharma et al., CaT: CAVS Traversability Dataset for Off-Road Autonomous Driving, 2022, IEEE, p. 24759-24768 (Year: 2022). [cited by examiner]
Carruth et al., Challenges in Low Infrastructure and Off-Road Automated Driving, 2022, IEEE, p. 13-20 (Year: 2022). [cited by examiner]
Giusti et al., A Machine Learning Approach to Visual Perception of Forest Trails for Mobile Robots, 2016, IEEE, p. 661-667 (Year: 2016). [cited by examiner]
Berteska, et al., “Photogrammetric Mapping Based on UAV Imagery”, Geodesy and Cartography, 2013, 6 pages. [cited by applicant]