- Demonstrator
AI Plant on Demand Demonstrator
Efficient and innovative AI technology
The AI Plant on Demand Demonstrator is investigating how robots use reinforcement learning to learn to harvest plants autonomously. Through repeated trial and error, they optimise their movements and actions until they can grasp and place objects with precision. This creates a learning system that improves itself and responds flexibly to changing conditions.
The demonstrator shows how AI can help to improve efficiency and conserve resources – in agriculture as well as in industrial applications. For students, our demonstrator offers a practical platform for applying modern learning algorithms and understanding how theoretical concepts are transformed into functioning robotic systems. The project was developed in collaboration with Salesforce and the Institute for Machine Tools and Industrial Management (iwb – TUM Munich).
Highlights
Video
Tools and technologies used
FAQ
What is the AI Plant on Demand Demonstrator?
The demonstrator investigates how robots use reinforcement learning to learn how to harvest crops autonomously. Through repeated trial and error, they optimise their movements until they are able to grasp and place objects with precision.
How does the learning principle behind it work?
The system is based on reinforcement learning: the robot repeatedly tries out different actions and improves autonomously in the process. This results in a learning system that reacts flexibly to changing conditions, rather than following rigidly programmed sequences.
Where can this technology be used?
The demonstrator shows how AI can help to improve efficiency and conserve resources – both in agriculture and in industrial applications involving similar gripping and placement tasks.
Who is behind the project?
The project was developed in collaboration with Salesforce and the Institute for Machine Tools and Industrial Management (iwb – TUM Munich) and offers students a practical platform on which to apply modern machine learning algorithms.