Row End Detection and Headland Turning Control for an Autonomous Banana-Picking Robot

A row-following system based on machine vision for a picking robot was designed in our previous study. However, the visual perception could not provide reliable information during headland turning according to test results. complete navigation working an orchard needs support accurate row following and turning. To fill this gap, method autonomous developed paper. Three steps were executed First, end detected vision. Second, deviation further reduced before using fast posture adjustment algorithm satellite information. Third, curve path tracking controller control. During MATLAB simulation experimental test, different controllers compared with method. The results show that enabled converge more quickly remain lower radial errors, which eventually led reductions time, space,