Jian Xu
Papers
1
Total Citations
9
H-Index
1
About
Jian Xu is a robotics researcher whose work centers on advanced manufacturing automation, with a particular focus on hybrid robot systems and intelligent trajectory generation for industrial applications. His most recognized contribution, "Grinding Trajectory Generation of Hybrid Robot Based on Cartesian Direct Teaching Technology" (2020), addresses a critical challenge in modern manufacturing: efficiently programming robots to grind components whose geometries are not predefined or modeled in advance. By developing a Cartesian space direct teaching methodology, Xu's approach enables operators to guide robots through grinding paths intuitively, eliminating the need for complex pre-programmed models and significantly lowering the barrier to deploying robotic grinding in flexible production environments. This work has garnered 9 citations since its publication, reflecting growing interest from the robotics and manufacturing communities in practical, user-friendly automation solutions. Xu's research sits at the intersection of human-robot interaction, motion planning, and precision machining — areas of increasing industrial relevance as manufacturers seek smarter, more adaptable robotic systems. His contributions offer meaningful pathways toward more accessible and efficient automation in real-world grinding and surface-finishing tasks.
Research Focus
Key Achievements
Top Papers
- 1