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About

Hongwen Xing is a leading researcher in intelligent manufacturing and robotic automation, with a focus on high-precision assembly and inspection for the aerospace industry. His work addresses critical challenges in aircraft component alignment, robotic drilling, and multi-view 3D measurement. Xing’s most influential contribution is the development of on-line calibration and uncertainty evaluation methods for spherical joint positions, enabling zero-clearance posture alignment of large aircraft components—a paper that has garnered 39 citations. He also pioneered a novel surface-normal measurement technique using three laser range sensors for robotic drilling on aircraft fuselages (23 citations), which has become essential for ensuring drilling accuracy. More recently, Xing has advanced positional error compensation for aviation drilling robots through Bayesian linear regression (22 citations) and introduced the MVGR (Mean-Variance Minimization Global Registration) method for multiview point cloud stitching in robot inspection (13 citations). His latest work on digital twin-based safety detection for human-robot collaboration in assembly (10 citations) reflects his growing impact on safe, intelligent manufacturing. With a portfolio of highly cited papers spanning from 2012 to 2024, Xing is recognized as a key innovator in robotic precision and aerospace automation.