Leaving the Lines Behind: Vision-Based Crop Row Exit for Agricultural
  Robot Navigation
Rajitha de Silva Grzegorz Cielniak Junfeng Gao
Usage of purely vision based solutions for row switching is not well explored
in existing vision based crop row navigation frameworks. This method only uses
RGB images for local feature matching based visual feedback to exit crop row.
Depth images were used at crop row end to estimate the navigation distance
within headland. The algorithm was tested on diverse headland areas with soil
and vegetation. The proposed method could reach the end of the crop row and
then navigate into the headland completely leaving behind the crop row with an
error margin of 50 cm.