AI helps to monitor and harvest strawberries

Strawberry season is already in full swing in Texas, while in other places, people await the arrival of this locally grown delight. While the early appearance of strawberries is enticing, it also underscores the importance of regional sourcing.

Embracing regional sourcing not only supports sustainable agriculture by requiring fewer resources and eliminating the need for chemicals, but it also signifies a forward-looking trend in farming.

This future trend in agriculture is already reality at a small family-owned farm in Czech Republic. The Ráje?ek family farm in Brno has introduced a groundbreaking participant in their agricultural process: Fravebot, a robot tasked with the monitoring and harvesting of strawberries.

However, with the adoption of such advanced technology comes the challenge of complexity in training, programming, controlling, and maintaining these robotic helpers. In this edition of Discover Digitalization, we introduce how Artificial Intelligence (AI) can step in here.

AI and robotics in the greenhouse?

The journey of a strawberry, from a small seed in the greenhouse to the delicious fruit found on supermarket shelves, is extensive and complex. It involves many steps and a lot of manual labor. Or rather it did. In their approach of revolutionizing strawberry harvesting with robotics, Ráje?ek farm uses two types of robots to make farming strawberries easier and more sustainable:? ?

• The Fravebot Scout for monitoring plant health and ripeness?
• The Fravebot Harvestor for picking the fruit?

“Dividing work tasks between two robot types is beneficial in many aspects,” explains Vratislav Bene?, Chief Constructor at Fravebot and the company's founder. “The Scouts, whose primary task is to monitor plants, move around the greenhouses faster, and if they were to do some other work simultaneously, it would delay them. It is the other way round – working robots work effectively in cases where they drive out only where they are needed."?

Fravebot stands for Fruit and Vegetable Robot, but internally the robot is affectionately called Franta. Students of the Brno University of Technology and the Mendel University in Brno were also involved in its development.?

Digital Twin in agriculture?

Additionally, a Digital Twin environment from NVIDIA plays a crucial role at the Ráje?ek farm, complementing the work of the robots. It helps develop, simulate, and deploy an AI that is meant to be the robots brain. Thanks to their training using the Digital Twin of plants and fruits in the NVIDIA Omniverse the robots are able to detect diseases and pests is the real world. The interface between real and digital world comes from the open digital business platform Siemens Xcelerator.?

As today’s simulation tools can also simulate physical laws (e.g., the weight of strawberries), the robot’s neural networks can be trained in advance without the need to move around the real environment. This approach significantly accelerates the robot development process and reduces costs. “I think that is the main path to follow: not to focus merely on the robotic part but also analytics and the user interface for plant growers,” emphasises Matěj Sklená?, Co-owner of Ráje?ek farm and Chief Agronomist of Hydroponic Cultivation.?

Thanks to a technology library, robot programming and control is easier than ever, eliminating the need to have two programming environments. This means the combination between the real and the digital worlds is closer and simpler than ever.

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