About

Zhaoxi Hong is a pioneering researcher at the intersection of human-robot collaboration and soft robotics, with a focus on advancing intelligent manufacturing for Industry 5.0. His work centers on constructing Human Digital Twin (HDT) models using multimodal data to enhance human-cyber-physical systems (HCPS), enabling robots to intuitively understand human locomotion and handover intentions. A key contribution is his development of a deep domain adaptation framework for human-robot handover tasks, which has garnered 17 citations for its potential to revolutionize adaptive collaboration. Hong has also made significant strides in soft robotics, designing origami-inspired reconfigurable soft actuators that achieve multi-degree-of-freedom motion (15 citations) and biomimetic actuators with rapid, programmable multi-stimulus response (14 citations). His most cited paper (33 citations) on HDT-based locomotion identification underscores his impact on creating safer, more efficient human-robot interactions. Through these innovations, Hong is shaping the future of smart manufacturing, where digital twins and soft actuators enable seamless, intuitive collaboration between humans and machines.

Research Focus

Key Achievements

4
H-Index
4
Papers
79
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
Construction of Human Digital Twin Model Based on Multimodal Data and Its Application in Locomotion Mode Identification
33 citations · 2023
📈 Most Prolific Year: 2024 (3 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Zhejiang Province Institute of Architectural Design and Research, Digital Science (United States), Guizhou University, Ningbo University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago