# Visual Servoing-based Navigation for Monitoring Row-Crop Fields

arXiv: https://arxiv.org/abs/1909.12754 · HTML: https://mlsanity.com/paper/1909.12754/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Sep 2019.

## Built on by (most cited first, 13 of 13)

- [RoboHop: Segment-based Topological Map Representation for Open-World Visual Navigation](https://mlsanity.com/paper/2405.05792/) (2024)
- [Agronav: Autonomous Navigation Framework for Agricultural Robots and Vehicles using Semantic Segmentation and Semantic Line Detection](https://mlsanity.com/paper/2304.04333/) (2023)
- [TANGO: Traversability-Aware Navigation with Local Metric Control for Topological Goals](https://mlsanity.com/paper/2509.08699/) (2025)
- [Towards Autonomous Visual Navigation in Arable Fields](https://mlsanity.com/paper/2109.11936/) (2021)
- [ObjectReact: Learning Object-Relative Control for Visual Navigation](https://mlsanity.com/paper/2509.09594/) (2025)
- [Towards agricultural autonomy: crop row detection under varying field conditions using deep learning](https://mlsanity.com/paper/2109.08247/) (2021)
- [Vision-based Vineyard Navigation Solution with Automatic Annotation](https://mlsanity.com/paper/2303.14347/) (2023)
- [Towards Infield Navigation: leveraging simulated data for crop row detection](https://mlsanity.com/paper/2204.01811/) (2022)
- [Deep learning-based Crop Row Detection for Infield Navigation of Agri-Robots](https://mlsanity.com/paper/2209.04278/) (2022)
- [Vision based Crop Row Navigation under Varying Field Conditions in Arable Fields](https://mlsanity.com/paper/2209.14003/) (2022)
- [A Vision-Based Navigation System for Arable Fields](https://mlsanity.com/paper/2309.11989/) (2023)
- [Leaving the Lines Behind: Vision-Based Crop Row Exit for Agricultural Robot Navigation](https://mlsanity.com/paper/2306.05869/) (2023)
- [Design of a six wheel suspension and a three-axis linear actuation mechanism for a laser weeding robot](https://mlsanity.com/paper/2512.10319/) (2025)

## Abstract (arXiv)

Autonomous navigation is a pre-requisite for field robots to carry out precision agriculture tasks. Typically, a robot has to navigate through a whole crop field several times during a season for monitoring the plants, for applying agrochemicals, or for performing targeted intervention actions. In this paper, we propose a framework tailored for navigation in row-crop fields by exploiting the regular crop-row structure present in the fields. Our approach uses only the images from on-board cameras without the need for performing explicit localization or maintaining a map of the field and thus can operate without expensive RTK-GPS solutions often used in agriculture automation systems. Our navigation approach allows the robot to follow the crop-rows accurately and handles the switch to the next row seamlessly within the same framework. We implemented our approach using C++ and ROS and thoroughly tested it in several simulated environments with different shapes and sizes of field. We also demonstrated the system running at frame-rate on an actual robot operating on a test row-crop field. The code and data have been published.