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 November 2023 our underwater robot team funded by SfTI travelled to Rotorua for a workshop which ran over three days at Novotel Lakeside and Te Puia. We listened to amazing speakers including Sir Ashley Bloomfield and Professor Rangi Mātāmua.
One morning our researchers Tim Rensen and Rory Clifford decided to film our underwater robot in Lake Rotorua. Rory was entering his video in a competition. Rory interviewed Tim and showed the robot being set up and operating in the lake. Rory attended the Video Media Training workshop, shot his video and ended up winning the prize for the best SfTI research video.
The trip was a very successful one and we are grateful to SfTI for funding our underwater ROV project.
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.
Tim and Timothy talk about the UC Vision ROV which has recently been taken to the Marlborough Sounds for fieldwork. The ROV has successfully scanned mussel lines in mussel farms as well as taking mussel samples from the ropes. Tim and Timothy explain the benefits of using an ROV in aquaculture.
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.