LandWISE 2015 Presenter Tom Botterill

Tom described advances in developing a viable grape vine pruning robot.  This work is through the MSI-funded project on “Vision Based Automated Pruning”.  Tom’s research interests include 3D reconstruction and modelling using computer vision.

Grape vines must be pruned every year in order to increase yield, prevent disease, and control excess growth. While some simple mechanical pruning systems are available, most of New Zealand’s winegrowers prefer to prune vines manually, even though hand-pruning is often the most expensive task in the vineyard.

To hand-prune a vine, the healthiest canes are selected and the rest are removed. For a robot to prune vines in this way, it must understand the 3D structure of the plant, it must be able to decide which canes to keep or remove, and it must be able to make the required cuts without damaging other canes.

A team at the University of Canterbury are developing just such a robot system. The system is mounted on a platform which straddles the vines and moves along the row, pruning as it goes. The robot uses three high resolution digital cameras to image the vines, then uses computer vision algorithms to make a 3D model of the vine from these images.

Given these vine models, an artificial intelligence system decides which canes to keep and which to cut. The artificial intelligence was “trained” to make good pruning decisions by providing it with examples of how pruning experts prune vines. To prune the vines, a six-jointed robot arm reaches amongst the canes and makes the required cuts with a spinning cutting tool.

The major technical challenges in the current system were building a 3D model of the complex vine structure, then reaching to cut the vines while the platform moves. After four years of development, the 3D models are finally complete and correct enough to make decisions about where to prune, however the dynamic robot arm control is still under development, so the robot must stop at each plant to make the cuts.

Our system has been made possible by rapid advances in computer vision and robot technology over the last decade, and it is close-to-working despite being far from the simplest way to automate pruning. The algorithms and techonology are now available to automate many harvesting, pruning and precision-agriculture tasks, and there are now no technical barriers to seeing all of these tasks automated out in the field.

This project is funded by MBIE and is a partnership between the University of Canterbury, NZ Winegrowers, Pernot Ricard NZ, Scott Technology, Lincoln University and the University of Otago.

Tom’s publications and more information: http://hilandtom.com/tombotterill/