Papers
2
Total Citations
10
H-Index
2
About
Yan Kai Tan is a researcher advancing the field of robotic assembly and computer vision, with a focus on automating precision manufacturing tasks. His work centers on two key areas: object detection for robotic manipulation and force-torque control strategies for high-precision assembly. Tan’s most cited paper, “Research on YOLOv8 Application in Bolt and Nut Detection for Robotic Arm Vision” (2024, 7 citations), addresses the critical first step in automated assembly—accurately detecting bolts and nuts within a robot’s workspace using state-of-the-art deep learning. This contribution is especially valuable given the scarcity of comprehensive data in this niche application. In his second notable work, “A Review of Advanced Force Torque Control Strategies for Precise Nut-to-Bolt Mating in Robotic Assembly” (2024, 3 citations), Tan systematically evaluates passive compliance, active control, and manual teaching methods for achieving micron-level alignment. By bridging computer vision and control theory, Tan is helping to enable robots to replace human labor in complex assembly tasks, with potential impacts on manufacturing efficiency and safety. His emerging body of work demonstrates a clear trajectory toward practical, industrially relevant solutions.
Research Focus
Key Achievements
Top Papers
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