Background:​

• The work tasks of the machine operator are changing: the automated machine is taking over more and more classic operating tasks, and the operator is increasingly organizing the processes around it (e.g. fleet management, farm management, private organizations). BUT: The farmer does not just want to sit in the office, but wants to be on site on the machine.​
• The cabin must be a motivating, attractive and modern workplace in order to continue to attract skilled workers to agriculture.​

• Autonomous field robots are set up and managed via PC / tablet – a concept for integration in a smart cabin does not yet exist.​

Challenge

• How does the driver get the (complex) processes and relevant information (e.g. obstacles or crop characteristics) visualized in an easy-to-grasp form and how can he interact with them safely and quickly?
• How can processes outside the cab (e.g. a fleet of field robots) be monitored and controlled – without losing control of their own machine?​
• What can a new form of human-machine interaction look like in this environment?​

Goal:

• Running prototype or functional mockup

Award:

• Paid PoC for 100 days (3 months)

Background:​

• The narrow ”Harvest window” of fieldwork poses a need for farmers to execute their work across the harvest chain (dept, road, field) as efficiently as possible.
• Complications arise when multiple machines and humans are present on and off the field, as current systems do not support inter-machine communication and planning.

Challenge

• Development of a multi-route planning algorithm that adjusts to the different levels of automation along the harvest chain.
• Optimization of the complete operation in terms of route and machine needs for efficiency (fastest), economy (cheapest), and environmental impact
• Creation of a 2D simulation to visualize the complete operation of the machines and the depot, showcasing the functionality of the algorithm.
• Illustration how the Farm Manager, the Combine Operator, and the Tractor Operator can interact with the system.

Goal:

• A system that optimizes the movements of the numerous machines, both autonomous and human-driven, involved in the entire harvest operation (depot, road, fields) and reduces threats from unpredicted behaviour and decisions by humans. A simulation of the harvest process will visualize the developed algorithm.

Award:

• Paid PoC