IP Library Granted Patent US 10,123,475
Granted Patent B2
US 10,123,475 · App. 15/423,811 · Granted Nov 13, 2018

System and method for automatically monitoring soil surface roughness

Inventors: John H. Posselius (Ephrata, PA); Luca Ferrari (Modena, IT); Taylor C. Bybee (Mendon, UT); Bret T. Turpin (Wellsville, UT)
Assignees: CNH Industrial America LLC; Autonomous Solutions, Inc.
A01B79/005A01B63/14B60W2300/152B60W2420/403B60W2420/52B60W2420/54B60W2422/95
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 10,123,475
App. No.
15/423,811
Granted
Nov 13, 2018
Kind
B2
Abstract

A method for automatically monitoring soil surface roughness as a ground-engaging operation is being performed within a field may include receiving pre-operation surface roughness data associated with a given portion of the field and receiving post-operation surface roughness data associated with the given portion of the field. In addition, the method may include analyzing the pre-operation and post-operation surface roughness data to determine a surface roughness differential associated with the performance of the ground-engaging operation and actively adjusting the operation of at least one of an associated work vehicle and/or implement when the surface roughness differential differs from a target set for the surface roughness differential.

Claims (37)

1. A method for automatically monitoring soil surface roughness as a ground-engaging operation is being performed within a field using a work vehicle towing an implement, the method comprising:

receiving, with one or more computing devices, pre-operation surface roughness data associated with a given portion of the field, the pre-operation surface roughness data corresponding to surface roughness data for the given portion of the field captured prior to the ground-engaging operation being performed thereon;

receiving, with the one or more computing devices, post-operation surface roughness data associated with the given portion of the field, the post-operation surface roughness data corresponding to surface roughness data for the given portion of the field captured after the ground-engaging operation has been performed thereon;

analyzing, with the one or more computing devices, the pre-operation and post-operation surface roughness data to determine a surface roughness differential associated with the performance of the ground-engaging operation; and

actively adjusting, with the one or more computing devices, the operation of at least one of the work vehicle or the implement when the surface roughness differential differs from a target set for the surface roughness differential.

2. The method of claim 1 , wherein the pre-operation surface roughness data and the post-operation surface roughness data is received by the one or more computing devices from at least one non-contact soil roughness sensor.

3. The method of claim 2 , wherein the at least one non-contact soil roughness sensor comprises at least one of a LIDAR scanner, a stereographic camera, an ultrasound device or a radar device.

4. The method of claim 2 , wherein receiving the pre-operation surface roughness data comprises receiving the pre-operation surface roughness data from a first non-contact soil roughness sensor provided in operative association with one of the work vehicle or the implement and wherein receiving the post-operation surface roughness data comprises receiving the post-operation surface roughness data from a second non-contact soil roughness sensor provided in operative association with the work vehicle or the implement.

5. The method of claim 4 , wherein the first non-contact soil roughness sensor is installed on one of the work vehicle or the implement at a location forward of a ground-engaging tool of the implement and the second non-contact soil roughness sensor is installed on one of the work vehicle or the implement at a location aft of the ground-engaging tool.

6. The method of claim 1 , further comprising:

receiving location data associated with at least one of the pre-operation surface roughness data or the post-operation surface roughness data; and

correlating the location data to the at least one of the pre-operation surface roughness data or the post-operation surface roughness data to generate or update a field map associated with the field.

7. The method of claim 1 , wherein analyzing the pre-operation and post-operation surface roughness data comprises:

analyzing the pre-operation surface roughness data to determine a pre-operation surface roughness value for the given portion of the field; and

analyzing the post-operation surface roughness data to determine a post-operation surface roughness value for the given portion of the field;

wherein the surface roughness differential is calculated based on the pre-operation and the post-operation surface roughness values.

8. The method of claim 7 , further comprising:

estimating a baseline ground surface as a function of at least one of the pre-operation surface roughness data or the post-operation surface roughness data; and

determining at least one of the pre-operation surface roughness value or the post-operation surface roughness value as a function of the baseline ground surface.

9. The method of claim 8 , wherein determining the at least one of the pre-operation surface roughness value or the post-operation surface roughness value as a function of the baseline ground surface comprises calculating the at least one of the pre-operation surface roughness value or the post-operation surface roughness value as a function of a standard deviation of vertical distances defined between the baseline ground surface and data points associated with the at least one of the pre-operation surface roughness data or the post-operation surface roughness data.

10. The method of claim 8 , wherein the baseline ground surface corresponds to a best-fit line that is fitted to the at least one of the pre-operation surface roughness data or the post-operation surface roughness data.

11. The method of claim 1 , further comprising analyzing at least one of the pre-operation surface roughness data or the post-operation surface roughness data to apply a sensor calibration or to remove data outliers.

12. A system for automatically monitoring soil surface roughness as a ground-engaging operation is being performed within a field using a work vehicle towing an implement, the system comprising:

at least one non-contact soil roughness sensor configured to capture data associated with a soil roughness of the field as the ground-engaging operation is being performed;

a controller commutatively coupled to the at least one non-contact soil roughness sensor, the controller including a processor and associated memory, the memory storing instructions that, when implemented by the processor, configure the controller to:

receive, from the at least one non-contact soil roughness sensor, pre-operation surface roughness data associated with a given portion of the field, the pre-operation surface roughness data corresponding to surface roughness data for the given portion of the field capture prior to the ground-engaging operation being performed thereon;

receive, from the at least one non-contact soil roughness sensor, post-operation surface roughness data associated with the given portion of the field, the post-operation surface roughness data corresponding to surface roughness data for the given portion of the field captured after the ground-engaging operation has been performed thereon;

analyze the pre-operation and post-operation surface roughness data to determine a surface roughness differential associated with the performance of the ground-engaging operation; and

actively adjust the operation of at least one of the work vehicle or the implement when the surface roughness differential differs from a target set for the surface roughness differential.

13. The system of claim 12 , wherein the at least one non-contact soil roughness sensor comprises at least one of a LIDAR scanner, a stereographic camera, an ultrasound device or a radar device.

14. The system of claim 12 , wherein the at least one non-contact soil roughness sensor comprises a first non-contact soil roughness sensor configured to capture the pre-operation surface roughness data and a second non-contact soil roughness sensor configured to capture the post-operation surface roughness data.

15. The system of claim 14 , wherein the first non-contact soil roughness sensor is installed on one of the work vehicle or the implement at a location forward of a ground-engaging tool of the implement and the second non-contact soil roughness sensor is installed on one of the work vehicle or the implement at a location aft of the ground-engaging tool.

16. The system of claim 12 , further comprising a positioning device communicatively coupled to the controller, the controller being configured to receive location data from the positioning device associated with at least one of the pre-operation surface roughness data or the post-operation surface roughness data and correlate the location data to the at least one of the pre-operation surface roughness data or the post-operation surface roughness data to generate or update a field map associated with the field.

17. The system of claim 12 , wherein the controller is configured to analyze the pre-operation surface roughness data to determine a pre-operation surface roughness value for the given portion of the field and analyze the post-operation surface roughness data to determine a post-operation surface roughness value for the given portion of the field, the surface roughness differential being calculated based on the pre-operation and the post-operation surface roughness values.

18. The system of claim 17 , wherein the controller is further configured to estimate a baseline ground surface as a function of at least one of the pre-operation surface roughness data or the post-operation surface roughness data and determine at least one of the pre-operation surface roughness value or the post-operation surface roughness value based on the baseline ground surface.

19. The system of claim 18 , wherein the controller is configured to calculate the at least one of the pre-operation surface roughness value or the post-operation surface roughness value as a function of a standard deviation of vertical distances defined between the baseline ground surface and data points associated with the at least one of the pre-operation surface roughness data or the post-operation surface roughness data.

20. The system of claim 18 , wherein the baseline ground surface corresponds to a best-fit line that is fitted to the at least one of the pre-operation surface roughness data or the post-operation surface roughness data.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 3, 2017
From: POSSELIUS, JOHN H.; FERRARI, LUCA; BYBEE, TAYLOR C.; TURPIN, BRET T.
To: CNH INDUSTRIAL AMERICA, LLC; AUTONOMOUS SOLUTIONS, INC.
Reel/Frame 041166/0357 →
Continuity (1)
Related Publication 20180220577A1 · Aug 9, 2018
Cited By (5)
US 12,342,740 US 12,461,083 US 12,464,967 US 12,696,829 US 12,721,252