Granted Patent B2

US 12,663,790 · App. 18/737,462 · Granted Jun 23, 2026

Inventors: Abraham Bachrach (Emerald Hills, CA); Adam Bry (Redwood City, CA); Matthew Donahoe (Redwood City, CA)

Assignee: Skydio, Inc.

G05D1/0016B64C39/024B64D47/08G01C21/1656G01C23/00G05D1/0027G05D1/0044G05D1/0094G05D1/223G05D1/225G05D1/689G05D1/692B64U10/10B64U10/13B64U30/20B64U2101/30B64U2201/10B64U2201/20

Abstract

Claims (40)

1 . A method for controlling an unmanned aerial vehicle (UAV), the method comprising:

tracking, by a processing system onboard the UAV, a pose or motion of a subject in a physical environment using image-based feature tracking, passive wireless localization, or inertial measurements of the UAV;

identifying, by the processing system, a preset gesture based on a detected change in the pose or motion of the subject, including correlating visual-odometry-derived feature motion with UAV inertial measurements to estimate a relative trajectory between the UAV and the subject; and

generating, onboard the UAV, control commands configured to cause the UAV to autonomously maneuver in a preset flight pattern corresponding to the preset gesture, the preset flight pattern being constrained to maintain a substantially constant radial distance from the subject in a spherical coordinate system; and

autonomously maneuvering the UAV in accordance with the generated control commands.

2 . The method of claim 1 , wherein tracking the subject includes detecting the subject using computer vision-based human recognition.

3 . The method of claim 1 , wherein tracking the subject includes device-free passive localization using changes to received wireless signals as the subject moves.

4 . The method of claim 1 , wherein identifying the preset gesture includes detecting arm-sweep motions of the subject.

5 . The method of claim 1 , wherein generating control commands includes applying feed-forward smoothing to predict the subject's intended trajectory.

6 . The method of claim 1 , wherein the UAV dynamically modifies the preset flight pattern based on detection of obstacles in the environment.

7 . The method of claim 1 , wherein the UAV maintains framing of the subject using a hybrid mechanical-digital gimbal.

8 . The method of claim 1 , wherein the UAV applies a visual-inertial odometry algorithm to estimate relative motion between the UAV and the subject.

9 . The method of claim 1 , wherein identifying the preset gesture includes detecting an azimuth-change gesture or an inclination-change gesture.

10 . The method of claim 1 , wherein the UAV maintains constant radial distance by constraining motion in a cylindrical coordinate system.

11 . A system for controlling an unmanned aerial vehicle (UAV), the system comprising:

a display;

one or more processors; and

one or more memory units having instructions stored thereon which, when executed by the one or more processors, cause the system to:

present a real-time three-dimensional reconstructed model of a physical environment generated using sensor data from the UAV;

identify a preset gesture of a subject based on a change in the subject's pose or motion detected from the reconstructed model;

interpret the preset gesture as a virtual-camera manipulation within the reconstructed model and generate control data defining a preset flight pattern corresponding to the manipulation, the preset flight pattern being dynamically modifiable; and

transmit the control data to the UAV.

12 . The system of claim 11 , wherein the reconstructed model comprises a textured mesh generated from depth and visual odometry data.

13 . The system of claim 11 , wherein the preset gesture includes a body-lean, arm-raise, or directional step detected within the model.

14 . The system of claim 11 , wherein the virtual-camera manipulation comprises orbit, pull-out, or sweep around a subject.

15 . The system of claim 11 , wherein the preset flight pattern is automatically replanned to maintain collision-free trajectories.

16 . The system of claim 11 , wherein the preset flight pattern comprises one or more preset aerial maneuvers.

17 . An unmanned aerial vehicle (UAV), comprising:

a first image capture device;

a propulsion system;

one or more processors; and

an autonomous navigation system configured to:

detect a preset gesture of a subject based on a change in the subject's pose or motion in a physical environment using image-based tracking, passive wireless localization, or depth estimation;

determine a relative position of the subject with respect to the UAV; and

autonomously maneuver the UAV in accordance with the detected gesture while maintaining a substantially constant radial distance from the subject in a spherical or cylindrical coordinate system.

18 . The UAV of claim 17 , wherein gesture detection includes using stereo depth estimation from the first image capture device.

19 . The UAV of claim 17 , wherein gesture detection uses optical-flow vectors of tracked subject features.

20 . The UAV of claim 17 , wherein maintaining constant radial distance includes adjusting UAV yaw and pitch while stabilizing captured images using a single-axis mechanical gimbal.

21 . The UAV of claim 17 , wherein the UAV autonomously recognizes a gesture to reposition and a gesture to change speed.

22 . The UAV of claim 17 , wherein the UAV generates a preset flight pattern using a learned model of prior subject gestures.

Assignments (2)

Continuity (7)

References Cited (174)