Xubing Chen
Papers
16
Total Citations
348
H-Index
9
About
Xubing Chen is a prominent robotics researcher whose work spans robot calibration, dynamic modeling, collaborative robotics, and intelligent manufacturing. His most recognized contribution, "A Dual Quaternion-Based Approach for Coordinate Calibration of Dual Robots in Collaborative Motion" (2020, 94 citations), introduced a mathematically elegant framework for solving the complex AXB=YCZ calibration problem in dual-robot systems—a fundamental challenge for achieving precise collaborative motion. Complementing this, his Lie theory-based methodologies for dynamic parameter identification and error modeling have provided more universal, computationally tractable alternatives to conventional robot modeling approaches, collectively accumulating over 90 citations. Chen has also made meaningful advances in robotic welding, developing techniques for D-type weld seam extraction from point clouds and dual-robot trajectory generation for intersecting pipe welding—practically significant contributions to industrial automation. His more recent work incorporates deep learning, notably a PSO-LSTM approach for joint torque prediction, and energy-efficient trajectory planning using metaheuristic optimization. Across more than 300 cumulative citations, Chen's research consistently bridges rigorous mathematical foundations with real-world industrial robotics applications, making his work particularly valuable to engineers and researchers advancing intelligent robotic manufacturing systems.
Research Focus
Key Achievements
Top Papers
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- 4A Method of D-Type Weld Seam Extraction Based on Point Clouds33 citations · 2021
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- 6Joint torque prediction of industrial robots based on PSO-LSTM deep learning19 citations · 2024
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