Online Prediction for Safe Human-Robot Collaboration: A Model of the Human Arm

Traditionally safety in industrial manufacturing environments has been addressed by rigid separation between robots and human operators. With the advent of new technologies and the transition of production to industry 4.0, a more flexible approach to manufacturing is pursued to achieve higher productivity, where robots and human operators are allowed to collaborate and interact. This transformation leads to overcoming traditional safety procedures and the development of new safety-assuring technologies for the minimization of risks connected with human robot collaboration. In this work we focus on the prediction of movements of operators’ upper torso and arms by developing a method which combines data driven methodologies with formal methods. The approach is based on a predictive model of human motion compared against the planned robot trajectory and online monitoring of satisfaction of safety requirements with formal methods. We provide an early assessment of the robustness of the proposed method with results from simulations in a virtual environment.