* Research on methods that answer the question “which industrial processes will benefit most by the human robot collaboration, based on specific KPIs“. The methodology will assess candidate industrial processes in a quantitative and qualitative manner, taking into account social aspects and human-related barriers and will identify those that are most suitable for collaborative workbenches based on specific KPI measures.
* Research and develop methodologies that answer the question “how should a cobot workbench be designed”. Identify the safety requirements for human robot collaboration – per collaboration type - and establish guidelines for the safe design of collaborative workbenches.
* Derive guidelines for the training of the workers in order to successfully and efficiently contribute in a cobot workbench.
* Research and develop machine-learning methodologies for cobot applications. These methodologies shall emulate disturbances and varying dynamic conditions during physical contact interaction. This should also integrate aspects of implicit communication between human and robot for interpreting forces/torques imparted by the worker on the robot.
* Research and develop advanced human robot interaction methodologies where interaction is accomplished using audio-gestural means.
* Adapt and integrate existing smart skin sensor technology and other smart sensors on the manipulator structure to enhance safety during physical human robot interaction.
* Research and develop multi-agent coordination where some of the agents (humans) are uncontrollable.
* Research and develop methodologies for safe cobot manipulation in close proximity to the worker, based on collision avoidance methods, especially for the type: Speed and Separation Monitoring (SSM).
* Research and develop methodologies for safe cobot manipulation and collaborative grasping involving physical contact with the worker especially for the collaboration type: Power and Force Limiting (PFL)