# Autonomous Navigation in Rows of Trees and High Crops with Deep Semantic Segmentation Source: [Autonomous Navigation in Rows of Trees and High Crops with Deep Semantic Segmentation]() Collection index: [llms.txt]() Data updated: 2025-10-26T02:23:12.204Z Authors: Alessandro Navone, Mauro Martini, Andrea Ostuni, Simone Angarano, Marcello Chiaberge Published: 2023-04-18T13:37:07.000Z ## Abstract Segmentation-based autonomous navigation has recently been proposed as a promising methodology to guide robotic platforms through crop rows without requiring precise GPS localization. However, existing methods are limited to scenarios where the centre of the row can be identified thanks to the sharp distinction between the plants and the sky. However, GPS signal obstruction mainly occurs in the case of tall, dense vegetation, such as high tree rows and orchards. In this work, we extend the segmentation-based robotic guidance to those scenarios where canopies and branches occlude the sky and hinder the usage of GPS and previous methods, increasing the overall robustness and adaptability of the control algorithm. Extensive experimentation on several realistic simulated tree fields and vineyards demonstrates the competitive advantages of the proposed solution. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. ## Original sources and implementation [Original paper]() [PDF]()