The mission of Digiforest is to develop the technology needed to achieve sustainable digital forestry. The following outlines four scientific ambitions which form the basis of our project.

They include fundamental development for (1) mobile robotic navigation (multi-sensor motion estimation, 3D mission planning) and (2) data-driven semantic mapping. (3) This highly detailed data will be presented to a human supervisor, enabling him/her to make informed decisions and (4) to plan the deployment of a mobile robot harvester to selectively intervene in an environmental manner.

For more information, please visit: digiforest.eu

Sestosenso develops technologies for next generations of collaborative robots capable of self-adapting to different time-varying operational conditions and capable of safe and smooth adaptation from autonomous to interactive when human intervention is required either for collaboration or training/teaching. The project proposes a new sensing technology from the hardware and up to the cognitive perception and control levels, based on networks of embedded proximity and tactile sensors on the robot body, providing a unified proxy-tactile perception of the environment, required to control the robot actions and interactions, safely and autonomously. Within the project, the same technologies are also applied to wearable devices (like exoskeletons) to provide the user with better spatial awareness and to enforce safety in critical human-robot interactive tasks.

FirstLab will be mainly involved in Use Case 3:
Agricultural harvesting via wearable devices and collaborative mobile manipulators

This project involves the development of Modular reconfigurable robots (MRRs). MRRs are composed of interchangeable mechatronic modules that can be rearranged to adapt a robot to operate under new circumstances, perform different tasks, or recover from damage. It is
anticipated the situations in which manually reconfigured MRRs will be deployed require the use of semi-automatic shared human-robot control. This work will involve developing a shared trajectory-tracking control system for an MRR.