Row following in pergola structured orchards

Abstract

Mobile service robots have the potential to improve the efficiency of fruit production in orchards. One of the key tasks that such robots must perform is traversing the rows. Many of the past implementations of row following in orchards have been developed for rows where the trees appear like walls on both sides. Another orchard structure that is used is the pergola, where a sparse array of trunks and posts hold up a canopy, which resembles a ceiling. Navigation in pergola structured environments has received less attention. The variations in the pergola environment- including the presence of tall weeds, hanging branches, undulating terrain and varying geometry-make following the rows a challenging problem. This paper presents solutions for finding the row centreline in pergola structured environments, in the presence of real world variability. A 3D laser scanner is used to measure the positions of posts and trunks, amongst the other features in the pergola. From the extracted features, the mode gradient of nearest neighbours is used to find the row direction and hence the centreline. The practicality of the system is demonstrated by autonomously driving a mobile robot through over 5000 meters of a kiwifruit orchard with a pergola structure, using the row detection method. This method performs favourably compared to an existing method of row detection in kiwifruit orchards.