Calibration of laser sensors

Patent metadata

Field	Value
Publication number	US-10859685-B2
Application number	US-201816171994-A
Country	US
Kind code	B2
Filing date	Oct 26, 2018
Priority date	Apr 28, 2017
Publication date	Dec 8, 2020
Grant date	Dec 8, 2020

Abstract

Automatic calibration of laser sensors carried by a mobile platform, and associated systems and methods are disclosed herein. A representative method includes determining an overlapping region of point cloud data generated by laser sensors, comparing surface features of the point clouds within the overlapping region, and generating calibration rules based thereon.

First claim

We claimed:

1. A computer-implemented method for calibrating at least a first emitter/detector unit and a second emitter/detector unit, both carried by a common mobile platform, the method comprising:
determining an overlapping region between a first point cloud and a second point cloud, the first point cloud and the second point cloud being projected into a coordinate system of the common mobile platform, wherein the first point cloud is determined from data generated by the first emitter/detector unit and the second point cloud is determined from data generated by the second emitter/detector unit;
comparing surface attributes of the first and second point clouds in the overlapping region; and
generating at least one calibration rule for calibration between the first and second emitter/detector units based at least in part on comparing the surface attributes, wherein the at least one calibration rule includes at least one of a translational transformation or a rotational transformation.

2. The method of claim 1 , wherein comparing surface attributes comprises matching a surface associated with the first point cloud with a surface associated with the second point cloud.

3. The method of claim 2 , wherein matching a surface associated with the first point cloud with a surface associated with the second point cloud comprises determining normal vector information with respect to at least a portion of the first point cloud.

4. The method of claim 1 , wherein comparing surface attributes further comprises evaluating a target function defined at least in part by a plurality of points of the first and second point clouds that are within the overlapping region.

5. The method of claim 4 , wherein the target function comprises a rotational component and a translational component.

6. The method of claim 5 , wherein comparing surface attributes further comprises keeping the translational component fixed.

7. The method of claim 4 , wherein generating at least one calibration rule comprises optimizing the target function.

8. The method of claim 7 , wherein optimizing the target function is based at least in part on a least squares method.

9. A non-transitory computer-readable medium storing computer executable instructions that, when executed, cause one or more processors associated with a mobile platform to perform actions comprising:
determining an overlapping region between a first point cloud and a second point cloud, the first point cloud and the second point cloud being projected into a coordinate system of the mobile platform, wherein the first point cloud is determined from data generated by a first emitter/detector unit and the second point cloud is determined from data generated by a second emitter/detector unit;
comparing surface attributes of the first and second point clouds in the overlapping region; and
generating at least one calibration rule for calibration between the first and second emitter/detector units based at least in part on comparing the surface attributes, wherein the at least one calibration rule includes at least one of a translational transformation or a rotational transformation.

10. The computer-readable medium of claim 9 , wherein the at least one calibration rule includes a rule for transformation between coordinate systems of the first emitter/detector unit and the second emitter/detector unit.

11. The computer-readable medium of claim 9 , wherein the actions further comprise detecting a difference between the generated at least one calibration rule and one or more previously generated calibration rules.

12. The computer-readable medium of claim 9 , wherein determining an overlapping region comprises determining one or more pairs of nearest neighbor points between the first point cloud and the second point cloud.

13. The computer-readable medium of claims 9 , wherein determining an overlapping region comprises creating a tree-shaped data structure for at least one of the first or second point clouds.

14. The computer-readable medium of claim 9 , wherein the mobile platform 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.

15. The computer-readable medium of claim 9 , wherein the actions further comprise causing calibration of the first and second emitter/detector units in accordance with the at least one calibration rule.

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:
determine an overlapping region between a first point cloud and a second point cloud, the first point cloud and the second point cloud being projected into a coordinate system of a mobile platform, wherein the first point cloud is determined from data generated by a first emitter/detector unit and the second point cloud is determined from data generated by a second emitter/detector unit;
compare surface attributes of the first and second point clouds in the overlapping region; and
generate at least one calibration rule for calibration between the first and second emitter/detector units based at least in part on comparing the surface attributes, wherein the at least one calibration rule includes at least one of a translational transformation or a rotational transformation.

17. The vehicle of claim 16 , further comprising the first emitter/detector, and wherein the first emitter/detector unit includes at least one laser sensor.

18. The vehicle of claim 17 , wherein the first emitter/detector unit includes a plurality of laser sensors rigidly fixed relative to each other.

19. The vehicle of claim 16 , wherein comparing surface attributes comprises determining normal vector information with respect to at least a portion of at least one of the first point cloud or the second point cloud.

20. The vehicle of claim 16 , wherein generating at least one calibration rule is based on optimizing a target function defined at least in part by the surface attributes of the first and second point clouds in the overlapping region.

Assignees

• Sz Dji Technology Co Ltd

Inventors

• Wu Kanzhi
• Ma Lu

Classifications

• G01B21/042

  Calibration or calibration artifacts (G01B3/30, G01B9/02072 take precedence) · CPC title

• G01B11/24

  for measuring contours or curvatures · CPC title

• G01S7/4808

  Evaluating distance, position or velocity data · CPC title

• G01S17/89

  for mapping or imaging · CPC title

• G01S7/4972 Primary

  Alignment of sensor · CPC title