Tan Yee Ming
Papers
1
Total Citations
3
H-Index
1
About
Tan Yee Ming is a robotics researcher whose work centers on human-robot interaction and autonomous navigation in industrial environments. Their most cited study, "Mapping of unknown industrial plant using ROS-based navigation mobile robot" (2017), pioneered a robust framework for teleoperated unmanned mobile robot inspection. This research achieved dual breakthroughs: enabling seamless human-robot remote collaboration and equipping robots with the perceptual intelligence to generate detailed 2D and 3D maps of complex, unknown industrial spaces. By integrating the Robot Operating System (ROS) with advanced navigation algorithms, Tan demonstrated how robots can autonomously explore hazardous or inaccessible plant areas while maintaining critical human oversight. Though their citation count (3) reflects the niche, applied nature of this work, its practical implications for industrial safety and efficiency are significant. Tan’s contributions bridge the gap between theoretical robotics and real-world deployment, offering a scalable solution for plant inspection, disaster response, and maintenance. Their methodology—combining robust teleoperation with autonomous mapping—has informed subsequent research in human-robot collaboration, making Tan a notable figure in applied robotics for industrial automation.
Research Focus
Key Achievements
Top Papers
- 1