The Underwater ROV team had a fieldtrip to Nelson in March. It was very successful with great weather over the week in Nelson and lots of data collected. The ROV scanned mussel rope lines at the mussel farms in Tasman Bay.
Autonomous scanning was refined to the point where we can accept early adopters. This is a massive milestone for spinning out our research into the real world.
In March the Occlusion project team had a trip to Lincoln University to learn about grapevine biology. As most of the team are computer scientists, a lesson was useful in learning about the different parts of the plant and what happens in different seasons.
We had a talk by Amber Parker from Lincoln University through very detailed slides. These were very informative, and the team were able to ask questions. We then went out into the vineyard which is currently covered with netting to protect the ripe fruit. Amber pointed out the features on the plants.
It was a very informative trip and we had time for a team photo before heading back to the UC campus.
On 14 February 2024 we held an event for the MBIE funded project, “Predicting the unseen: a new method for accurate yield estimation in viticulture/horticulture”, otherwise known as the Occlusion Project. The event was held at the NZ Wine Centre in Blenheim with talks on the project held in the theatre there and then a field trip to Constellation Vineyard to see our robot scanning the grapevines.
We had good industry engagement with lots of good discussion around what we are doing. The field trip was a great introduction to our robot ‘Matilda’ and camera bar. We hope to have this event yearly and invite more people next year as we build up a network of industry supporters.
In July 2023 we conducted our Maaratech field work in the Marlborough region.
Using our robot Genie, we scanned both sides of 110 plants in the Cloudy Bay vineyard.
The HDR capture coupled with the close alignment between each sides meant we got the best photos yet.
We also scan 1.5ha (approx. 3,000 vines) of vines at our secondary site:
In this vineyard we made use of the row following to achieve consistent distance from the vines.
We also tested our remote control of the vehicle. Here is a picture of Matt down the road having a coffee and monitoring the robot. The robot was autonomously scanning and no one was on site to monitor it.
Richie has now mounted all the camera’s on the adjustable camera bar onto Genie (see picture below). They still need some adjustment. Hopefully we will get to test this new set up in Lincoln in July.
The UC Computer Vision Lab’s project, headed by Professor Richard Green, is working on autonomously recording stereo vision of mussel lines. This footage is then post-processed, using advanced computer vision algorithms, to determine the mussel sizes and quantities, allowing for better crop forecasting. Tim Rensen, Ori Ganoni, and Timothy Manning spent a week in Marlborough sounds and Tasman Bay testing and rapidly prototyping new control and automation software. Some of the highlights of the trip were successfully scanning sections of the mussel farm autonomously and removing mussels from the line using a prototype gripper.
Matt Mattar has been on the UC Vision team for just over a year. We talked to him about what he does with programming robots for computer vision research which are used in vineyards. He talks about how he works on the front end of a database and doing the navigation stack for the robot. Fieldwork is a big part of the Maaratech project which he is working on. He describes what it is like out in the field.
Niels van Antwerpen did a 4th year project was to develop a detection and identification system. He trained an AI system to detect plants in a vineyard in order for the viticulturalist to go out into the vineyard and take photos and compare with photos in the past.
Niels has enjoyed Computer and software engineering at UC and working with the UC Vision team.
Watch the video of Niels talking about his time working with UC Vision.
The drone team had a trip on 23 August to Proseed in Amberley who kindly allowed us to test our drone onsite. Our final year project team with some industry support had made a cutting tool which comes out in front of the drone to cut pine catkins.
The Maaratech Team, both the University of Canterbury and University of Auckland teams, met in Blenheim last week for field work. The fieldtrip is still running this week, and it is hoped that a lot of data and insights will be gained from this trip.
The Maaratech project aims to reduce the variability of human worker performance in orchards and vineyards, using augmented reality technology to help inexpert workers make expert decisions, and reduce the risk associated with a transient workforce, using robotic automation. We will create new technologies that capture and convert data about plant structure, and the activities of expert humans, into smart decisions and actions in fruit growing e.g which grape vine to prune and how much to remove.
Today Sam Schofield and two researchers from Victoria University, Professor Peter Smith and Ikram Singh were collecting data to test the use of stochastic differential equations to model the motion of a drone during flight.
The drone was configured to fly autonomously along a specified flight path, while a motion capture system was used to measure its precise position and orientation.
This testing is part of the Drones Project funded by MBIE.
