This paper presents a robust navigation approach for autonomous agricultural robots based on LiDAR data. This navigation approach is divided into two parts: a find lines algorithm and a control algorithm. The paper proposes several find lines algorithms (based on PEARL/Ruby approach) that extract lines from a LiDAR data set. Once the lines have been processed from the data set, a control algorithm filters those lines and, using a fuzzy controller, generates the wheel speed commands to move the robot among the crop rows. This navigation approach was tested using a simulator based on ROS middle-ware and Gazebo (the source codes of that simulation are available on github). The results of the simulated experiments show that the proposed approach performs well for a large range of crop configurations (with or without considering weeds, with or without holes in the crop rows...).