Lang Liu
Papers
2
Total Citations
4
H-Index
2
About
Lang Liu’s research centers on advancing uncalibrated visual servoing for robot manipulators, with a particular focus on vision-based positioning and control systems that operate without prior knowledge of camera or robot parameters. In their 2015 work, Liu introduced a novel two-camera bi-axial parallel vision configuration that enables uncalibrated visual servoing, eliminating the need for real-time computation of the inverse image Jacobian—a significant step toward more flexible and autonomous robotic manipulation. Complementing this, their 2014 study developed a Kalman filter-based method for five-degrees-of-freedom uncalibrated vision positioning, allowing a robot manipulator to accurately determine its position and posture using fixed binocular cameras without requiring a pre-calibrated model. Though these foundational papers have garnered modest citation counts, they represent important contributions to the field of uncalibrated visual servoing, addressing key challenges in robotic autonomy and sensorimotor coordination. Liu’s work is particularly valuable for researchers exploring vision-guided robotics in unstructured environments, where traditional calibration is impractical.
Research Focus
Key Achievements
Top Papers
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