| Author(s) | Paper Title | Paper Details (journal name, publication year, volume, issue numbers, pages/paper number) |
|---|---|---|
| Li, C., Zheng, P.*, Li, S., Pang, Y.-M., Lee, K.M. | AR-assisted Digital Twin-enabled Robot Collaborative Manufacturing System with Humanin-the-loop |
Robotics and Computer-Integrated Manufacturing, 2022,76,102321. |
| Fan, J., Zheng P.*, Li, S. | Vision-based holistic scene understanding towards proactive human-robot collaboration |
Robotics and Computer-Integrated Manufacturing, 2022, 75, 102304. |
| Bao, Q., Zhao, G., Yu, Y., Zheng, P. | A node2vec-based graph embedding approach for unified assembly process information modeling and workstep execution time prediction |
Computers & Industrial Engineering, 2022, 163, 107864 |
| Li S. F., Zheng P.*, Fan J.M., Wang L. H. | Towards Proactive Human-Robot Collaborative Assembly: A Multimodal Transfer Learning-Enabled Approach |
IEEE Transactions on Industrial Electronics, 2022, 69(8): 8579-8587. |
| KL Keung, CKM Lee, P Ji | Industrial internet of things-driven storage location assignment and order picking in a resource synchronization and sharing-based robotic mobile fulfillment system |
Advanced Engineering Informatics, 2022, 52, 101540. |
| Wu CL, Xie WJ, Man HC | Laser additive manufacturing of biodegradable Mgbased alloys for biomedical applications: A review |
Journal of Magnesium and Alloys, 2022, 10(4), p915-937. |
| Zhang, R., Lv, J., Li, J., Bao, J., Zheng, P., & Peng, T | A graph-based reinforcement learning-enabled approach for adaptive human-robot collaborative assembly operations |
Journal of Manufacturing Systems, 2022, 63, 491-503. |
| Z Zhang, Q Han, Z Liu, X Wang, L Wang, X Yang, T Ma, Z Gao | Influence of the TiB2 content on the processability, microstructure and high-temperature tensile performance of a Ni-based superalloy by laser powder bed fusion |
Journal of Alloys and Compounds 908 (2022) 164656 |
| Liu, S., Sun, Y., Zheng, P.*, Lu, Y., Bao, J*. | Establishing a reliable mechanism model of the digital twin machining system: An adaptive evaluation network approach |
Journal of Manufacturing Systems, 2022, 62, 390401 |
| Zhang, J., Wang, Q., Su, Y., Jin, S., Ren, J., Eden, M., Shen, W. | An Accurate and Interpretable Deep Learning Model for Environmental Properties Prediction Using Hybrid Molecular Representations |
AIChE Journal, 2022, 68, 6, e17634. |
Journal Papers of RIAM
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