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Knowledge sharing enabled multirobot collaboration for preventive maintenance in mixed model assembly
journal contributionposted on 2022-09-20, 11:20 authored by Baotong Chen, Eve ZhangEve Zhang, Xuhui Xia, Miguel Martinez-GarciaMiguel Martinez-Garcia, Gbanaibolou Jombo
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.
Key Research and Development Program of Hubei Province (Grant Number: 2020BAA024)
Research on Dynamic Combination Mechanism of Remanufacturing Services for Generalized Growth of Waste Machinery Products
National Natural Science Foundation of ChinaFind out more...
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering
Published inIEEE Transactions on Industrial Informatics
Pages8098 - 8107
- AM (Accepted Manuscript)
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