System and method for determining field surface conditions using vision-based data and data from a secondary source

1. A system for determining field surface conditions, the system comprising:

a frame member;

a ground engaging tool coupled to the frame member, the ground engaging tool being configured to engage soil within a field as an agricultural implement is moved across the field;

a vision sensor having a field of view directed towards a portion of a surface of the field, the vision sensor generating vision-based data indicative of a field surface condition of the field;

a secondary sensor mounted to the ground engaging tool, the secondary sensor generating secondary data indicative of the field surface condition; and

a controller communicatively coupled to the vision sensor and the secondary sensor, the controller:

determining an initial surface condition associated with the field surface condition as a function of the vision-based data; and

determining a calibrated initial surface condition by calibrating the initial surface condition based at least in part on the secondary data generated by the secondary sensor.

2. The system of claim 1 , wherein the controller determines the calibrated initial surface condition by:

determining a correction factor based on the secondary data generated by the secondary sensor; and

determining the calibrated initial surface condition by applying the correction factor to the initial surface condition.

3. The system of claim 2 , wherein the correction factor is determined based at least in part on a differential between the initial surface condition determined as a function of the vision-based data and a second surface condition associated with the field surface condition, the second surface condition being determined as a function of the secondary data generated by the secondary sensor.

4. The system of claim 1 , wherein the controller further adjusts an operation of one or more components of the agricultural implement based at least in part on the calibrated initial surface condition.

5. The system of claim 1 , wherein the field surface condition is a soil surface roughness of the field and wherein the secondary sensor is provided in operative association with the ground engaging tool such that the secondary sensor detects a parameter indicative of movement of the ground engaging tool as the ground engaging tool rides along a surface of the field.

6. The system of claim 5 , wherein the ground engaging tool comprises at least one of a tine or a basket assembly of the agricultural implement.

7. The system of claim 5 , wherein the controller determines a first soil roughness for the field as a function of the vision-based data generated by the vision sensor and a second soil roughness for the field as a function of the secondary data generated by the secondary sensor,

the controller further:

determining a correction factor based on the first and second soil roughnesses, and

utilizing the correction factor to calibrate subsequent soil surface roughnesses determined as a function of the vision-based data generated by the vision sensor.

8. The system of claim 1 , wherein the secondary sensor comprises at least one of an accelerometer, a load sensor, or a rotational sensor.

9. The system of claim 1 , wherein the vision sensor comprises at least one of a camera or a LIDAR device.

10. The system of claim 1 , wherein the field of view of the vision sensor is directed towards an aft portion of the field relative to the agricultural implement in a direction of travel of the agricultural implement.

11. A method for determining field surface conditions, the method comprising:

receiving, with one or more computing devices, vision-based data indicative of a field surface condition of a field;

receiving, with the one or more computing devices, secondary data indicative of the field surface condition, the secondary data being generated by a secondary sensor mounted to a ground engaging tool of an agricultural implement, the ground engaging tool being configured to engage soil within the field as the agricultural implement is moved across the field;

determining, with the one or more computing devices, an initial surface condition associated with the field surface condition as a function of the vision-based data;

determining, with the one or more computing devices, a calibrated initial surface condition by calibrating the initial surface condition based at least in part on the secondary data; and

adjusting, with the one or more computing devices, an operation of one or more components of the agricultural implement based at least in part on the calibrated initial surface condition.

12. The method of claim 11 , wherein determining the calibrated initial surface condition comprises determining a correction factor based at least in part on a differential between the initial surface condition and a second surface condition determined as a function of the secondary data.

13. The method of claim 12 , wherein determining the calibrated initial surface condition further comprises adjusting the initial surface condition using the correction factor.

14. The method of claim 11 , wherein the field surface condition is a soil surface roughness of the field, the secondary sensor being provided in operative association with the ground engaging tool such that the secondary sensor detects a parameter indicative of movement of the ground engaging tool as the ground engaging tool rides along a surface of the field.

15. The method of claim 14 , wherein the ground engaging tool comprises at least one of a tine or a basket assembly of the agricultural implement.

16. The method of claim 11 , wherein the secondary sensor comprises at least one of an accelerometer, a load sensor, or a rotational sensor.

17. The method of claim 11 , wherein the vision-based data is generated by a vision sensor, the vision sensor being provided in operative association with the agricultural implement and having a field of view directed towards a portion of a surface of the field.

18. The method of claim 17 , wherein the field of view of the vision sensor is directed towards an aft portion of the field relative to the agricultural implement in a direction of travel of the agricultural implement.

19. The method of claim 17 , wherein the vision sensor comprises at least one of a camera or a LIDAR device.