Knowledge sharing enabled multirobot collaboration for preventive maintenance in mixed model assembly

This paper focuses on knowledge driven techniques, and it proposes a Knowledge Sharing-enabled Multi- Robot Collaboration (KS-enabled MRC) strategy for preventive maintenance of robots in Mixed Model Assembly (MMA). Firstly, a formal semantic environment for MMA is constructed by way of ontology-enabled semantic modeling. Then, task-related action primitives and ontology-based robot skill bases are established according to robot capability and task environment. Finally, the Wu-Palmer similarity metric and first-order logic are leveraged to match and reason new tasks according to the semantic rules, and a knowledge sharing and update mechanism is developed for this application. Experimental results demonstrate that the proposed KS-enabled MRC can reduce unscheduled downtime and assist in achieving a load balance for robots in MMA. It can potentially avoid severe equipment degradation, thus acting as a preventive maintenance paradigm. Furthermore, it is applicable across different platforms and exhibits high deployment efficiency without intense programming requirements.