Tree centric localisation in almond orchards
Robotics and intelligent sensing systems can provide useful information to improve yield and quality in specialty crop production. A key requirement for tree-crop applications is the ability to associate sensed data to the individual trees in an orchard. A mobile ground robot with a scanning lidar (laser range sensor) is used to build a three dimensional (3D) model of an orchard and algorithms are derived to automatically detect and segment each tree. The height profile of each canopy is used to match the tree to a previously obtained database, to determine the location of the robot in the orchard, and to associate newly obtained agronomic data to the existing database. Experiments were conducted over 16 months in a 2.3 ha section of an almond orchard in Mildura, Victoria. An average tree segmentation accuracy of 99.1% was obtained, and the localisation accuracy was 98.2% for data obtained one full year apart. The method is sufficiently accurate to provide a feasible mechanism for localisation and data management in orchard environments.
Underwood, J.P., Jagbrant, G., Nieto, J. and Sukkarieh, S. (2016). Tree centric localisation in almond orchards. Acta Hortic. 1130, 619-624
robotics, sensing, precision-agriculture, intelligent information systems