Papers
2
Total Citations
7
H-Index
2
About
Junnan Wang’s research centers on robotics, teleoperation, and visual feedback control, with a focus on enhancing the precision and autonomy of robotic systems. His major contributions include the development of an internet-based, visual feedback networked robot arm teleoperation system, which integrates image transmission and processing modules to achieve closed-loop control for a 2-DOF manipulator. This work, cited 4 times, addresses key challenges in semi-closed-loop networked systems by enabling real-time visual monitoring and end-effector recognition. Wang also advanced localization and control algorithms for robot arms with visual feedback, achieving sub-pixel precision through improved camera calibration techniques and an enhanced SUSAN detection method. This research, cited 3 times, demonstrates his ability to refine computer vision algorithms for practical robotics applications. While his citation counts reflect a focused, early-career impact, Wang’s work lays important groundwork for networked telerobotics and vision-guided manipulation—areas critical to modern automation and remote surgery. His achievements highlight a commitment to bridging theoretical algorithms with real-world robotic systems, offering valuable insights for students and researchers exploring the intersection of control theory, computer vision, and human-robot interaction.
Research Focus
Key Achievements
Top Papers
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