News
Training AI with 3D fish: building blocks for fishing industry automation
In a few years, fishing vessels will be equipped with cameras and robots that were developed using synthetic data and machine learning. Researcher Arjan Vroegop speaks about automation in the fishing industry, game engines, Masenro 3, and how to count fish even if you can’t see them all.
Plaice fall in a jumble onto a conveyor belt along with stones, shells, and other species of fish. Flop, there is another fish falling across the computer screen. Then a shell falls from the top of the screen and another one, and then we see more fish tumbling over each other. Behind the controls of the simulation is Vision+Robotics researcher Arjan Vroegop. “We are using synthetic data to ‘train’ a robot so it can learn the difference between plaice and by-catch (unwanted fish), among other things.”
Vroegop created the simulation with his colleagues at WANDER lab, a Wageningen University & Research group focusing on virtual and augmented reality. They created 3D fish for a virtual environment. On his screen several more plaice are passing by on the conveyor belt. Vroegop: “That conveyor belt moves underneath a camera, enabling us to automatically record data. Our goal is to ‘teach’ the robot to identify the species of fish it sees. Even if they are poorly visible or hidden.”
- Unfortunately, your cookie settings do not allow videos to be displayed. - check your settings