Trunk localisation in trellis structured orchards

Information gathering and processing in horticulture helps optimise control processes and can enable more precise farm management.
Robotics and automation are helping make high resolution, timely, farm wide measurements for tasks such as yield estimation, crop health and soil analysis.
An efficient means of storing and processing such information is to discretise it to individual trees.
To automate this process, an unmanned ground vehicle was deployed at a commercial apple orchard near Melbourne, Australia.
The robot captured three dimensional (3D) laser range data and image data over orchard rows spanning an area of 1.6 ha.
The area contained different apple cultivars on two types of trellis systems, a vertical I-trellis structure and a modern Güttingen V-trellis structure.
Initially, tree trunk candidates (representative of the individual trees) were detected within the 3D laser range data.
These candidates were then projected onto images taken at the corresponding locations to confirm their presence.
By repeating this over individual orchard rows, a tree inventory was built over the farm.
The experimentation was done at different times of the year and for different apple cultivars and trellis structures.
A trunk localisation accuracy ranging from 89-96% was obtained during the pre-harvest season and there was near perfect performance (99% accuracy) during the flowering season, which is sufficient for building a tree inventory over a trellis structured orchard.

XXIX International Horticultural Congress on Horticulture: Sustaining Lives, Livelihoods and Landscapes (IHC2014): International Symposia on the Physiology of Perennial Fruit Crops and Production Systems and Mechanisation, Precision Horticulture and Robotics

S. Bargoti, J.P. Underwood, J. Nieto, S. Sukkarieh

robotics, sensing, precision-agriculture, intelligent information systems

https://doi.org/10.17660/ActaHortic.2016.1130.93