IP Library Granted Patent US 12,416,918
Granted Patent B2
US 12,416,918 · App. 18/463,149 · Granted Sep 16, 2025

Unmanned aerial image capture platform

Inventors: Hayk Martirosyan (San Francisco, CA); Adam Bry (Redwood City, CA); Matthew Donahoe (Redwood City, CA); Abraham Bachrach (Emerald Hills, CA); Justin Michael Sadowski (Menlo Park, CA)
Assignee: Skydio, Inc.
G05D1/0094G05D1/106G06T7/292B64U2101/30B64U2201/10G06T2207/10021G06T2207/10032G06T2207/30252
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Quick Facts
Patent No.
US 12,416,918
App. No.
18/463,149
Granted
Sep 16, 2025
Kind
B2
Abstract

Methods and systems are disclosed for an unmanned aerial vehicle (UAV) configured to autonomously navigate a physical environment while capturing images of the physical environment. In some embodiments, the motion of the UAV and a subject in the physical environment may be estimated based in part on images of the physical environment captured by the UAV. In response to estimating the motions, image capture by the UAV may be dynamically adjusted to satisfy a specified criterion related to a quality of the image capture.

Claims (48)

1. A method comprising:

capturing, by multiple image sensors of a vehicle, images of a physical environment surrounding the vehicle;

processing the images of the physical environment surrounding the vehicle to identify images with overlapping fields of view;

processing the images with overlapping fields of view to identify dense correspondences between the images, wherein the dense correspondences indicate matches between pixels in the images with overlapping fields of view;

estimating distances to the pixels in the images with overlapping fields of view using the identified dense correspondences; and

generating and continually updating a three-dimensional (3D) map of the physical environment based on the estimated distances.

2. The method of claim 1 , further comprising:

causing the vehicle to autonomously navigate through the physical environment based, at least in part, on the 3D map of the physical environment.

3. The method of claim 1 , wherein the images of the physical environment surrounding the vehicle are captured during sequential time steps.

4. The method of claim 1 , wherein the images of the physical environment surrounding the vehicle are stereoscopic images captured during a same timestep and the multiple image sensors are configured with pre-defined spatial offsets.

5. The method of claim 1 , further comprising:

estimating a relative position of the vehicle within the physical environment while simultaneously continually updating the 3D map.

6. The method of claim 1 , further comprising:

estimating an orientation of the vehicle within the physical environment while simultaneously continually updating the 3D map.

7. The method of claim 1 , further comprising:

estimating a relative position of a subject within the physical environment while simultaneously continually updating the 3D map.

8. The method of claim 1 , further comprising:

estimating an orientation of a subject within the physical environment while simultaneously continually updating the 3D map.

9. A vehicle comprising:

multiple image sensors configured to capture images of a physical environment surrounding the vehicle;

a control system configured to continually:

process the images of the physical environment surrounding the vehicle to identify images with overlapping fields of view;

process the images with overlapping fields of view to identify dense correspondences between the images, wherein the dense correspondences indicate matches between pixels in the images with overlapping fields of view;

estimate distances to pixels in the images with the overlapping fields of view using the identified dense correspondences; and

update a three-dimensional (3D) map of the physical environment based on the estimated distances.

10. The vehicle of claim 9 , wherein the control system is further configured to:

generate the 3D map of the physical environment based on the estimated distances.

11. The vehicle of claim 9 , wherein the control system is further configured to:

cause the vehicle to autonomously navigate through the physical environment based, at least in part, on the 3D map of the physical environment.

12. The vehicle of claim 9 , wherein the images of the physical environment surrounding the vehicle are captured during sequential time steps.

13. The vehicle of claim 9 , wherein the images of the physical environment surrounding the vehicle are stereoscopic images captured during a same timestep and the multiple image sensors are configured with pre-defined spatial offsets.

14. The vehicle of claim 9 , wherein the control system is further configured to:

estimate a relative position of the vehicle and/or a subject within the physical environment while simultaneously continually updating the 3D map.

15. The vehicle of claim 9 , wherein the control system is further configured to:

estimating an orientation of the vehicle and/or a subject within the physical environment while simultaneously continually updating the 3D map.

16. The vehicle of claim 9 , wherein the multiple image sensors are arranged to provide a 360 degree view around the vehicle, and wherein the multiple image sensors are arranged such that at least two image sensors are provided with overlapping fields of view.

17. An apparatus, comprising:

one or more memory units storing instructions that, when executed by one or more processors of a vehicle, cause the one or more processors to:

process images of a physical environment surrounding the vehicle to identify images with overlapping fields of view;

process the images with overlapping fields of view to identify dense correspondences between the images, wherein the dense correspondences indicate matches between pixels in the images with overlapping fields of view;

estimate distances to pixels in the images with the overlapping fields of view using the identified dense correspondences; and

generate and continually update a three-dimensional (3D) map of the physical environment based on the estimated distances.

18. The apparatus of claim 17 , wherein the instructions, when executed by the one or more processors of the vehicle, further cause the one or more processors to:

cause the vehicle to autonomously navigate through the physical environment based, at least in part, on the 3D map of the physical environment.

19. The apparatus of claim 17 , wherein the instructions, when executed by the one or more processors of the vehicle, further cause the one or more processors to:

estimate a relative position of the vehicle and/or a subject within the physical environment while simultaneously continually updating the 3D map.

20. The apparatus of claim 17 , wherein the instructions, when executed by the one or more processors of the vehicle, further cause the one or more processors to:

estimate an orientation of the vehicle and/or a subject within the physical environment while simultaneously continually updating the 3D map.

Assignments (2)
SECURITY INTEREST Recorded Dec 5, 2024
From: SKYDIO, INC.
To: ACQUIOM AGENCY SERVICES LLC
Reel/Frame 069516/0452 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 8, 2023
From: MARTIROSYAN, HAYK; BRY, ADAM; DONAHOE, MATTHEW; BACHRACH, ABRAHAM; SADOWSKI, JUSTIN MICHAEL
To: SKYDIO, INC.
Reel/Frame 064837/0853 →
Continuity (5)
Continuation 17899459 · Aug 30, 2022
Continuation 17388828 · Jul 29, 2021
Continuation 16723549 · Dec 20, 2019
Continuation 15235513 · Aug 12, 2016
Related Publication 20240069547A1 · Feb 29, 2024
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