3D collision avoidance strategy and performance evaluation for human–robot collaborative systems. (May 2023) - Boschetti, Giovanni; Faccio, Maurizio; Granata, Irene; Minto, Riccardo
Abstract: Collaborative robots (cobots) are one of the newest technologies helpful to improve the performance of the systems. This is because of their ability to combine the high-level productivity, typical of automatic machines, with the flexibility, typical of manual systems. Moreover, they can work directly with human operators, in the same work area; however, the shared workspace is both the greatest advantage and limit of collaborative robots. In collaborative applications it is important to understand how this interaction between different resources can affect the performance of the system since an emergency stop can be generated due to interference between them, reducing so the efficiency of the system. Indeed, a collision avoidance strategy can be introduced in order to promote the prosecution of the movement, but safely. Therefore, a 3D collision avoidance strategy is presented in this work, which is experimentally validated to prove the goodness of the proposed method. Finally, the performance of the systems is investigated through simulation and experimental tests to comprehend the effects of the dimension of the collaboration area with respect to the workspace. From the results, it is possible to understand that the reduction in performance, because of an increase in the collaboration area, is mitigated by the introduction of the collision avoidance strategy, since fewer emergency stops are required. Highlights: New model for 3D collision avoidance strategy for collaborative robotics cells. Design of an experimental setup with motion capture technology. Performance evaluation of the effect of collision avoidance on the system performance. Extensive case study for the model application.