# Leaving the Lines Behind: Vision-Based Crop Row Exit for Agricultural Robot Navigation

arXiv: https://arxiv.org/abs/2306.05869 · HTML: https://mlsanity.com/paper/2306.05869/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 14 references that are in the map.
- First posted on arXiv 9 Jun 2023.

## Builds on (most cited first, 3 of 3)

- [k-Nearest Neighbour Classifiers: 2nd Edition (with Python examples)](https://mlsanity.com/paper/2004.04523/) (2020)
- [Visual Servoing-based Navigation for Monitoring Row-Crop Fields](https://mlsanity.com/paper/1909.12754/) (2019)
- [Vision based Crop Row Navigation under Varying Field Conditions in Arable Fields](https://mlsanity.com/paper/2209.14003/) (2022)

## Abstract (arXiv)

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.