Revolutionising Agriculture Robotics with 3D Deep Learning
Why 3D Deep Learning?
As far as physics goes, we live in a world of three dimensions—the x, y and z of everyday coordinates. For millennia, natural selection has given humans the ability to see things in height, length and width. Our vision allows us to connect with our surroundings and complete daily tasks efficiently and safely. From hunting to gathering to food production, we continue to meet our basic needs because of this ability.
As one of the world’s oldest professions, the agriculture industry still depends on workers’ vision to perform a range of farming activities: planting, cutting, pruning and harvesting to name a few. However, the quality of labour and the shortage of workers affects the productivity, profitability and scalability of food production. Ushering in a new age of agriculture, we are finding more and more ways to replicate the human visual system to automate and robotise even the most complex crop work activities.
Robovision has been a pioneer in 3D deep learning, a technological revolution for building state-of-the-art agriculture robotics. Combining multiple camera 3D vision technology and deep learning techniques, we are developing a new generation of agricultural robots together with our OEM partners. It’s a whole new range of agriculture robotics that can plant, harvest, prune and keep learning.
Making your algorithms modular
Our 3D deep learning software makes agricultural robots in greenhouses around the world see exactly which bulb to plant or crop to harvest.
Combining multiple 2D RGB and depth cameras, we build a 3D model that gives us much more data and thus much higher accuracy rates.
RETRAIN, THEN SCALE
Robovision AI puts the power of deep learning in the hands of plant experts. Through the platform, they can easily retrain their models to use on different crops.
READY TO INTEGRATE
Combining our platform and a team that knows all the ins and outs of both algorithms and crops, we build robust pipelines and sturdy setups.