Prediction of operator intentions by action forecasting in collaborative assembly tasks

The logic of Industry 4.0 foresees humans and robots as indistinguishable parts of a larger heterogeneous body of distributed autonomous and cooperative entities. Under such a perspective, robots are endowed with self and environment awareness and are able to smartly interact with both humans and other machines. Consequently, and in contrast to the third industrial revolution, machines are not intended to substitute humans in industry, but to work with them in synergy. In collaborative industrial scenarios, safety greatly depends on the reciprocal understanding between the human operator and the robotic system. On the one hand, the operator needs to be aware of the collaborative robot’s motion to guarantee him or her own safety. On the other, the robot must identify, understand and forecast operator’s actions to promptly react and safely adapt to either expected or unexpected operative conditions. Under the assumption that operator’s intentions are mainly focused on completing the assigned task, such intentions can be predicted in terms of the sequence of actions required to complete it. Therefore, intentions forecasting greatly relies on the ability of the robotic system to promptly identify tasks executed by the operator and to model the transitions between them. Moreover, beyond normal operative conditions, it is of fundamental regard to identify unexpected operator’s actions to avoid any dangerous circumstance.https://youtu.be/WCpjHs_Bl1