Jia-Bin Pan
Papers
6
Total Citations
217
H-Index
6
About
Jia-Bin Pan is a leading researcher in robotic systems, specializing in dual-robot coordination, calibration, and visual servoing. His work addresses fundamental challenges in collaborative robotics, particularly through the use of advanced mathematical frameworks like dual quaternions and Lie theory. Pan’s most influential contribution is a novel dual quaternion-based approach for coordinate calibration in dual-robot collaborative motion, published in 2020 and cited 94 times, which solves the complex AXB=YCZ problem to enable precise hand-eye, robot-robot, and tool-flange alignment. He also developed a Lie-theory-based dynamic parameter identification methodology for serial manipulators (50 citations), offering a universal solution for accurate robot dynamics modeling. Pan’s practical impact extends to industrial applications, including simulation and trajectory generation for dual-robot collaborative welding of intersecting pipes, and the creation of RobMach, a G-code-based off-line programming system for robotic machining. His recent work on simultaneous coordinate calibrations using LMI-SDP optimization (18 citations) and infinite homography-based uncalibrated visual servoing (IHUVS) further advances visually-guided robotic manipulation. With over 200 total citations, Pan’s research bridges theoretical rigor and real-world robotics, making him a key figure in advancing collaborative and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
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