Correction of motion-based inaccuracy in point clouds

Patent metadata

Field	Value
Publication number	US-11238561-B2
Application number	US-201816145173-A
Country	US
Kind code	B2
Filing date	Sep 28, 2018
Priority date	Jul 31, 2017
Publication date	Feb 1, 2022
Grant date	Feb 1, 2022

Abstract

Correcting motion-based inaccuracy in point cloud data generated by one or more sensors carried by a scanning platform, and associated systems and methods are disclosed herein. A representative method includes associating a motion model with a target object of the point cloud, estimating adjusting factors based on the motion model, and adjusting scanning points in the point cloud using the adjusting factors.

First claim

We claim:

1. A computer-implemented method for adjusting point clouds generated using at least one scanner carried by a scanning platform, the method comprising:
obtaining base point cloud information comprising a plurality of scanning points that are produced by the scanner, wherein each of at least a subset of the scanning points indicates a position of at least a portion of a target object and wherein at least two scanning points of the plurality of scanning points are produced at different times;
assessing the base point cloud information to determine estimated motion model factors;
relocating one or more scanning points of the plurality of scanning points based, at least in part, on an estimated motion of the target object in accordance with a motion model associated with the target object and in accordance with the determined estimated motion model factors;
generating an adjusted point cloud based, at least in part, on the relocating of the one or more scanning points;
determining an error distance of the adjusted point cloud;
comparing the error distance to a threshold; and
determining a maximum time period for generating the adjusted point cloud based on the comparison.

2. The method of claim 1 , further comprising determining the estimated motion of the target object based, at least in part, on a volume defined by the plurality of scanning points.

3. The method of claim 2 , wherein the volume defined in accordance with the plurality of scanning points includes a minimized quantity of volume pixels occupied by the scanning points at a target timepoint, in accordance with the motion model associated with the target object.

4. The method of claim 2 , wherein the volume defined in accordance with the plurality of scanning points includes a minimized volume enclosed by the scanning points at a target timepoint, in accordance with the motion model associated with the target object.

5. The method of claim 1 , wherein the plurality of scanning points is produced within a period of time.

6. The method of claim 5 , wherein a relative distance between the target object and the scanning platform changes during the period of time.

7. The method of claim 5 , wherein the adjusted point cloud represents at least one of a location, orientation, or shape of the target object at the end of the period of time.

8. The method of claim 1 , wherein the estimated motion of the target object includes at least one of a translational motion or a rotational motion.

9. The method of claim 1 , further comprising locating the target object based, at least in part, on the adjusted point cloud.

10. A non-transitory computer-readable medium storing computer-executable instructions that, when executed, cause one or more processors associated with a scanning platform to perform actions, the actions comprising:
obtaining base point cloud information comprising a plurality of scanning points that are produced by at least one scanner, wherein each of at least a subset of the scanning points indicates a position of at least a portion of a target object and wherein at least two scanning points of the plurality of scanning points are produced at different times;
assessing the base point cloud information to determine estimated motion model factors;
relocating one or more scanning points of the plurality of scanning points based, at least in part, on an estimated motion of the target object in accordance with a motion model associated with the target object and in accordance with the determined estimated motion model factors;
generating an adjusted point cloud based, at least in part, on the relocating of the one or more scanning points;
determining an error distance of the adjusted point cloud;
comparing the error distance to a threshold; and
determining a maximum time period for generating the adjusted point cloud based on the comparison.

11. The computer-readable medium of claim 10 , wherein the positions indicated by at least two of the scanning points correspond to different portions of the target object.

12. The computer-readable medium of claim 10 , wherein the scanning points are represented within a three-dimensional reference system associated with the at least one scanner or the scanning platform.

13. The computer-readable medium of claim 10 , wherein the actions further comprise estimating a motion of the target object based, at least in part, on the motion model that includes at least one of a translational motion component or a rotational motion component.

14. The computer-readable medium of claim 13 , wherein the translational motion component includes at least one of a constant translational speed factor or a variable translational speed factor.

15. The computer-readable medium of claim 13 , wherein the rotational motion component includes at least one of a constant rotational speed factor or a variable rotational speed factor.

16. A vehicle including a controller programmed to at least partially control one or more motions of the vehicle, wherein the programmed controller includes one or more processors configured to:
obtain base point cloud information comprising a plurality of scanning points that are produced by at least one scanner, wherein each of at least a subset of the scanning points indicates a position of at least a portion of a target object and wherein at least two scanning points of the plurality of scanning points are produced at different times;
assess the base point cloud information to determine estimated motion model factors;
relocate one or more scanning points of the plurality of scanning points based, at least in part, on an estimated motion of the target object in accordance with a motion model associated with the target object and in accordance with the determined estimated motion model factors;
generate an adjusted point cloud based, at least in part, on the relocating of the one or more scanning points;
determine an error distance of the adjusted point cloud;
compare the error distance to a threshold; and
determine a maximum time period for generating the adjusted point cloud based on the comparison.

17. The vehicle of claim 16 , wherein the one or more processors are further configured to determine the estimated motion of the target object based, at least in part, on a volume defined by the plurality of scanning points.

18. The vehicle of claim 16 , wherein the plurality of scanning points is produced within a period of time.

19. The vehicle of claim 18 , wherein the adjusted point cloud represents at least one of a location, orientation, or shape of the target object at the end of the period of time.

20. The vehicle of claim 16 , wherein the vehicle includes at least one of an unmanned aerial vehicle (UAV), a manned aircraft, an autonomous car, a self-balancing vehicle, a robot, a smart wearable device, a virtual reality (VR) head-mounted display, or an augmented reality (AR) head-mounted display.

Assignees

• Sz Dji Technology Co Ltd

Inventors

• Li Chen
• Ma Lu

Classifications

• G01S7/4808 Primary

  Evaluating distance, position or velocity data · CPC title

• G06V2201/12

  Acquisition of 3D measurements of objects · CPC title

• G06V20/56

  exterior to a vehicle by using sensors mounted on the vehicle · CPC title

• G06V20/64

  Three-dimensional [3D] objects · CPC title

• G06T2207/10028

  Range image; Depth image; 3D point clouds · CPC title