Runjia Tan
Papers
7
Total Citations
112
H-Index
4
About
Runjia Tan is an emerging researcher at the forefront of human-robot collaboration, intelligent manufacturing, and autonomous robotic systems. His work is particularly focused on disassembly planning within Industry 5.0 frameworks, where he champions human-centric manufacturing through the integration of Human-Cyber-Physical Systems (HCPS). His most influential contribution, "A human-cyber-physical system enabled sequential disassembly planning approach for a human-robot collaboration cell in Industry 5.0" (2023), has garnered 72 citations, demonstrating significant community recognition of his efforts to bridge human expertise with robotic precision in shared workspaces. Tan has further advanced the field through personalized disassembly sequence planning, addressing the mass personalization paradigm increasingly demanded by modern industry. Beyond disassembly, Tan has broadened his research into robotic perception, developing category-agnostic instance detection methods for flexible smart factory environments. His more recent investigations explore the integration of Large Language Models (LLMs) into robotic manipulation and human-robot interaction, enhanced by augmented reality interfaces and IoT-enabled autonomous navigation. Together, these contributions position Tan as a versatile innovator working to make robots more adaptive, intelligent, and genuinely collaborative partners in next-generation manufacturing environments.
Research Focus
Key Achievements
Top Papers
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- 3Human-robot interactive disassembly planning in Industry 5.0<sup>*</sup>6 citations · 2023
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