Xuechao Duan
Papers
13
Total Citations
166
H-Index
8
About
Xuechao Duan is a leading researcher in the field of cable-driven parallel robots (CDPRs) and precision positioning systems. His work focuses on solving fundamental challenges in workspace analysis, kinematic calibration, and robust control for these complex robotic systems. Duan’s seminal 2014 paper on workspace classification and quantification of CDPRs (31 citations) established a foundational framework for understanding the dynamic capabilities of cable robots, a critical step for their application in large-scale tasks. He has also made significant contributions to visual SLAM, developing a robust loop closure detection method that integrates visual, spatial, and semantic information via topological graphs and CNN features (29 citations). His impact is further demonstrated by his work on the calibration and motion control of a triple-level spatial positioner for the Five-hundred-meter Aperture Spherical radio Telescope (FAST) project (27 citations), and his innovative use of machine learning—such as kernel extreme learning machines for forward kinematics (8 citations)—to solve long-standing problems in parallel robotics. With over 150 total citations, Duan’s research bridges theoretical analysis and practical deployment, advancing the capabilities of cable-driven and parallel manipulators in demanding applications like radio astronomy and industrial sorting.
Research Focus
Key Achievements
Top Papers
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