Ming‐Zhe Dai

Papers

Total Citations

H-Index

About

Ming-Zhe Dai is a leading researcher in robotics and computer vision, with a core focus on hand-eye calibration (HEC)—a critical technique for precision industrial visual servoing and robotic grasping. His most influential work, "Globally Optimal Symbolic Hand-Eye Calibration" (2020, 18 citations), addresses a long-standing challenge in the field. While prior approaches relied on closed-form or iterative solutions with various pose parameterizations, these methods often suffered from local optima or lacked robustness. Dai pioneered a globally optimal symbolic framework that guarantees convergence to the true solution, dramatically improving accuracy and reliability in real-world robotic systems. This breakthrough has direct implications for high-stakes applications like automated assembly and surgical robotics, where millimeter-level precision is non-negotiable. Beyond this landmark paper, Dai’s research bridges theoretical optimization and practical deployment, earning recognition for advancing the mathematical foundations of calibration. His work is essential reading for engineers and researchers seeking to push the boundaries of autonomous manipulation, and his citation record underscores its growing influence in both academia and industry.