Scanning Mussel Ropes

Our UC Computer Vision group is involved with the project “Precision Farming Technology for Aquaculture” let by Cawthron Institute/Chris Cornelisen. This project involves the scanning of mussel ropes using an autonomous vehicle.

Autonomous Underwater Scanner

An autonomous underwater vehicle (AUV) for surveying  

At the University of Canterbury, we have developed an autonomous underwater vehicle that can be easily operated by novice users to remotely inspect underwater structures to enable surveys, inspections and use manipulation tools and sensors without human assistance. This can now do rapid 3D colour scanning/recognition of underwater surfaces / objects / organisms to sub-mm accuracy using novel AI approaches to automatically ‘scan’ for crop health, condition, biofouling, or conditions of underwater structures.

So far, we have used this AUV for mussel farm surveying to estimating crop size/health, salmon net surveying to scan for holes in nets and wharf pylon surveying for biosecurity inspections.

mussel ropes
salmon net
biofouling on a wharf pylon

Following is a video of an ROV autonomously scanning mussel ropes:

Our approach is unique in that we have developed an advanced AUV simulator which enables rapid prototyping of novel navigation, inspection patterns and AI-based image recognition. This software-in-the-loop code runs line-for-line in both the simulator and underwater drone. This, together with our extensive experience in AI and developing AUVs, gives us a significant advantage, not only in NZ, but internationally.

Collectively we will have all the necessary capability in sensing / integration, marine engineering, AUV design, control systems, 3D vision analysis, AI (especially deep learning expertise), autonomous software, and field deployment to enable rapid prototyping and development of novel applications.