Papers
15
Total Citations
241
H-Index
9
About
Jingjing Xu is a robotics researcher whose work sits at the intersection of robot motion planning, intelligent assembly automation, and human-robot collaboration. With a focus on industrial manipulation tasks, Xu has made significant contributions to solving real-world challenges in automated assembly and disassembly, particularly for bolt and peg-in-hole operations under complex or uncertain working conditions. Among Xu's most impactful contributions is the development of a noncontact hybrid vision-guided control strategy for circular peg-in-hole assembly (42 citations), which addresses critical limitations in adaptability and efficiency faced by existing robotic assembly methods. Complementing this, Xu's work on collision detection using convex-plane-polygon representations (40 citations) and minimum-distance calculations for workspace safety (18 citations) has advanced the practical deployment of industrial manipulators. Trajectory planning innovations grounded in screw theory (27 citations) and stiffness-aware modeling further demonstrate a commitment to precision and efficiency in robot operation. Xu has also contributed a well-regarded review of intelligent bolt assembly technologies (26 citations), synthesizing progress in a domain where automation promises to dramatically reduce labor intensity. Collectively, Xu's publication record, spanning over 200 citations, reflects growing influence in smart manufacturing robotics, making this body of work highly relevant to students and engineers advancing the next generation of autonomous industrial systems.
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