Shan Xu
Papers
2
Total Citations
12
H-Index
2
About
Shan Xu is a robotics researcher whose work addresses fundamental challenges in controlling soft and reconfigurable robotic systems. His primary research areas include model-less control methods, task space trajectory tracking, and orientation constraint problems in robotics. Xu’s major contribution lies in tackling the Incomplete Orientation Constraint (IOC)—a persistent challenge arising from the nonlinear structure of the rotation group SO(3), which complicates motion control when not all spatial directions are constrained. His 2020 paper, “On Perpendicular Curve-Based Model-Less Control Considering Incomplete Orientation Constraint,” has garnered 8 citations, establishing a foundational approach to this problem. Building on this, his 2022 work, “On Perpendicular Curve-Based Task Space Trajectory Tracking Control With Incomplete Orientation Constraint,” with 4 citations, extends the methodology to real-time trajectory tracking. Xu’s innovative use of perpendicular curves offers a novel geometric solution to IOC, enabling more precise and adaptable control for emerging robotic platforms. His work is particularly impactful for applications in soft robotics, where traditional model-based approaches often fail, making him a notable contributor to the future of autonomous, flexible robotic systems.
Research Focus
Key Achievements
Top Papers
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