In this paper we propose a novel model-based control method for an autonomous agricultural vehicle that operates in tree fruit orchards. The method improves path following performance by taking into account the vehicle's motion model, including the effects of wheel sideslip, to calculate speed and steering commands. It also generates turn paths that improve visibility of the orchard rows, thus increasing the probability of a successful turn from one row into another, while respecting maximum steering rate limits. The method does not depend on GPS signals for either state estimation or path following, relying instead only on data from a planar laser scanner and wheel and steering encoders. This makes it suitable for real agricultural applications where acquisition cost is key to a farmer's decision to invest in new technologies. We show the controller's stability using Lyapunov functions and demonstrate its feasibility in experiments conducted in an orchard-like nursery. (C) 2015 Elsevier B.V. All rights reserved.