Method for autonomous detection of crop location based on tool depth and location

A method comprising, at an autonomous machine:

• capturing a first image of a ground area of a plant bed surface via a ground-facing camera arranged on the autonomous machine;
• detecting a first target plant in the first image;
• accessing a lateral pixel location of the first target plant in the first image;
• via a depth sensor arranged on the autonomous machine, estimating a depth of a subregion of the ground area, comprising:
• at the depth sensor, capturing a depth image of the subregion of the ground area;
• identifying a ground region of the depth image;
• and
• calculating an average depth of the ground region based on the ground region of the depth image;
• for each tool module in a set of tool modules in contact with the plant bed surface and arranged behind the ground-facing camera relative to a direction of forward motion of the autonomous machine:
• capturing an extension distance of the tool module;
• and
• capturing a lateral position of the tool module relative to the ground-facing camera;
• estimating a surface profile of the plant bed surface based on the extension distance of each tool module in the set of tool modules and the lateral position of each tool module in the set of tool modules;
• estimating a depth profile based on the surface profile and the depth of the subregion of the ground area;
• estimating a real lateral location of the first target plant relative to the autonomous machine based on the lateral pixel location of the first target plant and the depth profile of the plant bed surface;
• and
• driving a first tool module in the set of tool modules to a lateral position laterally aligned with the real lateral location of the first target plant.

A method comprising, at an autonomous machine:

• capturing a first image of a ground area of a plant bed surface via a ground-facing camera arranged on the autonomous machine;
• detecting a first target plant in the first image;
• accessing a lateral pixel location of the first target plant in the first image;
• via a depth sensor arranged on the autonomous machine, estimating a depth of a subregion of the ground area;
• for each tool module in a set of tool modules in contact with the plant bed surface and arranged behind the ground-facing camera relative to a direction of forward motion of the autonomous machine:
• capturing an extension distance of the tool module;
• and
• capturing a lateral position of the tool module relative to the ground-facing camera;
• estimating a surface profile of the plant bed surface based on the extension distance of each tool module in the set of tool modules and the lateral position of each tool module in the set of tool modules;
• estimating a depth profile based on the surface profile and the depth of the subregion of the ground area;
• estimating a real lateral location of the first target plant relative to the autonomous machine based on the lateral pixel location of the first target plant and the depth profile of the plant bed surface;
• and
• driving a first tool module in the set of tool modules to a lateral position laterally aligned with the real lateral location of the first target plant;
• at a second time, capturing an extension distance of a first weeding module in the set of tool modules;
• and
• estimating a first depth of blades of the first weeding module based on a difference between the depth of the subregion of the ground area and the extension distance of the first weeding module.