Method and apparatus for support surface edge detection

• US 10,572,763 B2
• Filed: 09/07/2017
• Issued: 02/25/2020
• Est. Priority Date: 09/07/2017
• Status: Active Grant

• Current Assignee: Symbol Technologies, LLC (Zebra Technologies Corporation)
• Original Assignee: Symbol Technologies, LLC (Zebra Technologies Corporation)
• Inventors: Rzeszutek, Richard Jeffrey
• Primary Examiner(s): Hsieh, Ping Y
• Application Number:
  US15/698,361
• Publication Number:
  US 20190073554A1
• Time in Patent Office: 901 Days
• CPC Class Codes: G01S 17/06 Systems determining position data of a target
• CPC Class Codes: G01S 17/42 Simultaneous measurement of distance and other co-ordinates indirect measurement G01S17/46
• CPC Class Codes: G01S 17/86 Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
• CPC Class Codes: G01S 17/89 for mapping or imaging
• CPC Class Codes: G01S 7/4808 Evaluating distance, position or velocity data
• CPC Class Codes: G06K 7/10792 Special measures in relation to the object to be scanned
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: G06V 20/00 Scenes; Scene-specific elements control of digital cameras H04N23/60
• CPC Class Codes: G06V 20/10 Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59

Abstract

A method of detecting an edge of a support surface by an imaging controller includes: obtaining a plurality of depth measurements captured by a depth sensor and corresponding to an area containing the support surface; selecting, by the imaging controller, a candidate set of the depth measurements based on at least one of (i) an expected proximity of the edge of the support surface to the depth sensor, and (ii) an expected orientation of the edge of the support surface relative to the depth sensor; fitting, by the imaging controller, a guide element to the candidate set of depth measurements; and detecting, by the imaging controller, an output set of the depth measurements corresponding to the edge from the candidate set of depth measurements according to a proximity between each candidate depth measurement and the guide element.

Claims

1. A method of detecting an edge of a shelf by an imaging controller, the edge of the shelf facing into an aisle, the method comprising:

obtaining a plurality of depth measurements captured by a depth sensor positioned in the aisle, the depth measurements defining distances from the depth sensor to respective points on the shelf;

selecting, by the imaging controller, a candidate set of the depth measurements based on at least one of (i) an expected proximity of the edge of the shelf to the depth sensor, and (ii) an expected orientation of the edge of the shelf relative to the depth sensor;

fitting, by the imaging controller, a guide element to the candidate set of depth measurements; and

detecting, by the imaging controller, an output set of the depth measurements that lie on the edge of the shelf from the candidate set of depth measurements according to a proximity between each candidate depth measurement and the guide element.

2. The method of claim 1, wherein obtaining the depth measurements comprises obtaining a lidar scan including, for each of a plurality of sweep angles, a respective group of the depth measurements.

3. The method of claim 2, wherein selecting the candidate set further comprises, for each sweep angle, selecting a single minimum depth measurement from the group corresponding to the sweep angle.

4. The method of claim 3, wherein obtaining the depth measurements comprises obtaining a plurality of lidar scans each including, for each of the plurality of sweep angles, a respective group of the depth measurements;

and

wherein selecting the candidate set further comprises, for each sweep angle, selecting a single minimum depth measurement from the plurality of groups corresponding to the sweep angle.

5. The method of claim 2, wherein fitting the guide element comprises fitting a curve to the candidate set of depth measurements.

6. The method of claim 5, wherein fitting the curve to the candidate set of depth measurements comprises at least one of:

minimizing a depth of the curve; and

maximizing a population of the candidate depth measurements intersected by the curve.

7. The method of claim 2, wherein detecting the output set comprises:

determining, for each candidate depth measurement, a distance between the candidate depth measurement and the guide element;

identifying local minima among the distances; and

selecting the candidate depth measurements corresponding to the local minima.

8. The method of claim 1, wherein obtaining the depth measurements comprises obtaining a depth image including a plurality of pixels each containing one of the depth measurements.

9. The method of claim 8, wherein selecting the candidate set of depth measurements comprises:

subdividing the depth image into a plurality of patches;

generating normal vectors for each of the patches; and

selecting the depth measurements contained in patches having normal vectors with a predetermined orientation.

10. The method of claim 8, wherein fitting the guide element comprises:

at each of a predetermined sequence of depth ranges, fitting a plane to the candidate depth measurements within the depth range; and

selecting one of the planes intersecting the greatest number of the candidate depth measurements.

11. The method of claim 10, wherein detecting the output set of depth measurements comprises selecting the candidate depth measurements that are intersected by the one of the planes.

12. A computing device for detecting an edge of a shelf, the edge facing into an aisle, the computing device comprising:

a memory; and

an imaging controller including;

a preprocessor configured to obtain a plurality of depth measurements captured by a depth sensor positioned in the aisle, the depth measurements defining distances from the depth sensor to respective points on the shelf;

a selector configured to select a candidate set of the depth measurements based on at least one of (i) an expected proximity of the edge of the shelf to the depth sensor, and (ii) an expected orientation of the edge of the shelf relative to the depth sensor;

a guide generator configured to fit a guide element to the candidate set of depth measurements; and

an output detector configured to detect an output set of the depth measurements that lie on the edge of the shelf from the candidate set of depth measurements according to a proximity between each candidate depth measurement and the guide element.

13. The computing device of claim 12, wherein the preprocessor is configured to obtain the depth measurements by obtaining a lidar scan including, for each of a plurality of sweep angles, a respective group of the depth measurements.

14. The computing device of claim 13, wherein the selector is configured to select the candidate set by, for each sweep angle, selecting a single minimum depth measurement from the group corresponding to the sweep angle.

15. The computing device of claim 14, wherein the preprocessor is further configured to obtain the depth measurements by obtaining a plurality of lidar scans each including, for each of the plurality of sweep angles, a respective group of the depth measurements;

and

wherein the selector is further configured to select the candidate set by, for each sweep angle, selecting a single minimum depth measurement from the plurality of groups corresponding to the sweep angle.

16. The computing device of claim 13, wherein the guide generator is configured to fit the guide element by fitting a curve to the candidate set of depth measurements.

17. The computing device of claim 16, wherein the guide generator is configured to fit the curve to the candidate set of depth measurements by at least one of:

minimizing a depth of the curve; and

maximizing a population of the candidate depth measurements intersected by the curve.

18. The computing device of claim 13, wherein the output detector is configured to detect the output set by:

determining, for each candidate depth measurement, a distance between the candidate depth measurement and the guide element;

identifying local minima among the distances; and

selecting the candidate depth measurements corresponding to the local minima.

19. The computing device of claim 12, wherein the preprocessor is configured to obtain the depth measurements by obtaining a depth image including a plurality of pixels each containing one of the depth measurements.

20. The computing device of claim 19, wherein the selector is configured to select the candidate set of depth measurements by:

subdividing the depth image into a plurality of patches;

generating normal vectors for each of the patches; and

selecting the depth measurements contained in patches having normal vectors with a predetermined orientation.

21. The computing device of claim 19, wherein the guide generator is configured to fit the guide element by:

at each of a predetermined sequence of depth ranges, fitting a plane to the candidate depth measurements within the depth range; and

selecting one of the planes intersecting the greatest number of the candidate depth measurements.

22. The computing device of claim 21, wherein the output detector is configured to detect the output set of depth measurements by selecting the candidate depth measurements that are intersected by the one of the planes.