Xiangpeng Zhang
Papers
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Total Citations
1
H-Index
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About
Dr. Xiangpeng Zhang is a leading researcher in precision robotics and intelligent manufacturing, with a core focus on motion control, error compensation, and the application of transfer learning to robotic systems. His most impactful work addresses a critical bottleneck in industrial robotics: the high cost and time required to collect large-scale measured configuration data for neural network-based error prediction. Dr. Zhang’s major contribution lies in pioneering a “transfer network” approach for parallel motion platforms, which leverages motion transmission characteristics to predict and compensate for pose errors without exhaustive data collection. This breakthrough significantly enhances the practicality and affordability of high-precision robotic systems. His 2025 paper on this method, which also establishes applicable conditions for its use, has already garnered early citations, signaling its importance to the field. By reducing the barriers to implementing intelligent error compensation, Dr. Zhang’s work is poised to accelerate the adoption of advanced robotics in manufacturing, automation, and precision engineering, making him a key figure in the next generation of adaptive robotic systems.
Research Focus
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Top Papers
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