Xiaolin Zhong

Edinburgh Napier University, Chongqing University of Posts and Telecommunications

Papers

Total Citations

150

H-Index

About

Xiaolin Zhong is a pioneering researcher in the field of robotics, with a primary focus on robot calibration and autonomous localization. His most influential work centers on developing innovative methods for kinematic identification and on-site calibration of industrial manipulators. In the mid-1990s, Zhong introduced a groundbreaking approach using artificial neural networks for inverse robot calibration, a paper that has garnered 58 citations and remains a foundational reference in the field. He further advanced the discipline with his autonomous calibration technique employing a trigger probe, which allowed for precise joint sensor measurements without external metrology systems—a concept detailed in two highly cited works (49 and 39 citations). This method significantly improved the practicality of calibration in real-world industrial environments. More recently, Zhong has extended his expertise to mobile robotics, proposing an adaptive square root cubature Kalman filter for simultaneous localization and mapping (SLAM). This algorithm enhances the robustness and accuracy of state estimation in dynamic environments. With a career spanning from foundational calibration theory to modern SLAM solutions, Zhong’s work has consistently pushed the boundaries of autonomous robot precision and reliability.