  Achieving success in agricultural activities heavily relies on precise
navigation in row crop fields. Recently, segmentation-based navigation has
emerged as a reliable technique when GPS-based localization is unavailable or
higher accuracy is needed due to vegetation or unfavorable weather conditions.
It also comes in handy when plants are growing rapidly and require an online
adaptation of the navigation algorithm. This work applies a segmentation-based
visual agnostic navigation algorithm to lavender fields, considering both
simulation and real-world scenarios. The effectiveness of this approach is
validated through a wide set of experimental tests, which show the capability
of the proposed solution to generalize over different scenarios and provide
highly-reliable results.
