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arXiv · 1909.12754

Visual Servoing-based Navigation for Monitoring Row-Crop Fields

Alireza Ahmadi·Lorenzo Nardi·Nived Chebrolu·Cyrill Stachniss
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Abstract

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.

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Alireza Ahmadi, Lorenzo Nardi, Nived Chebrolu, Cyrill Stachniss. 2019-09-27. Visual Servoing-based Navigation for Monitoring Row-Crop Fields. https://arxiv.org/abs/1909.12754

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