What is the role of FGI in the FEROX project?

Key roles of FGI in FEROX include the development of berry yield maps and leading the validation of FEROX technologies for value creation and demonstrating them for berry picking cases studies. For yield maps, FGI combines various data sources that can be used to model wild berry yields.

How can geospatial, robotics and AI solutions support the overall aims of FEROX?

There is a large number of environmental factors affecting wild berry yield, such as  elevation and slope, stand characteristics, especially canopy cover and age and amount of shadowing trees and scrubs, forest site types and species compositions, and history of silvicultural treatments. That information can be provided by geospatial solutions. Robotics provides the autonomous platforms for sensors needed in the mapping, and AI provided automated image processing for the mapped data.

How can drone-based LiDAR contributing in the project tasks? 

Under-canopy drones are used to collect field reference data, images showing the number of berries. FGI sees that in future, we will have personal drone assistants, that can collect real-time information of the berry and mushroom picker's neighbourhood. That means the pickers can get information where to go next in order to improve the speed of data collection.