This project will move the research front within field robotics by developing new methods and knowledge in the cross section between 3D sensing, deep learning, control, and safety assurance, which will enable robust and efficient interaction with agricultural crops. By working on real use-cases and data from the start, we ensure relevance for the industry and end-users, and are forced to focus on real-world challenges using sensor data and incorporating reliability measures.
The project will do this through developing new knowledge within the whole cycle from sensing to interaction:
- Accurate 3D sensing in highly varying outdoor settings for moving platforms.
- Learning-based 3D analysis for robotic interaction.
- Design and control of a compact multi-arm robotic system on a moving platform.
- Safety and reliability of autonomous operation.
There is a need for new knowledge on how to combine uncertainty of sensors, learning-based components, and control, to ensure the overall reliability of the system in an unstructured and changing environment.
The work will be performed in close collaboration between research partners (SINTEF and NMBU), robot companies (Saga Robotics, RobotNorge, Byte Motion), end-users (farmers), and strategic international research partners (e.g., University of Lincon).