  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.
