In the last years, mobile robots have emerged as an alternative solution for increasing the levels of automation and mechanization in agricultural fields. In this context, the key idea of precision agriculture is to optimize the use of production inputs, crop losses, waste of water and to increase the crop production in small areas, in an efficient and sustainable manner. Agricultural robots or AgBots may be autonomous or remotely controlled, being endowed with different types of locomotion apparatus, actuation and sensory systems, as well as specialized tools which enable them to carry out a number of agricultural tasks such as, seeding, pruning, harvesting, phenotyping, monitoring and data collection. In this work, we perform a study on two type of wheeled mobile robots (i.e., differential-drive and car-like) and their application for autonomous navigation in agricultural fields. The modeling and control design is based on classical and advanced approaches, using robust control approaches such as Sliding Mode Control (first order) and Super Twisting Algorithm (second order) to deal with parametric uncertainties and external disturbances, commonly founded in agricultural fields. Verification and validation are carried out by means of numerical simulations in MATLAB and 3D computer simulations in Gazebo. Preliminary experimental tests are included to illustrate the performance and feasibility of the proposed modeling and control methodologies. Concluding remarks and perspectives are presented to summarize the strengths and weaknesses of the proposed solution and to suggest the scope for future improvements.