Papers
1
Total Citations
6
H-Index
1
About
Chenxuan Xu is a researcher advancing the field of industrial robotics and sensor calibration, with a focus on enhancing precision and reliability in automated systems. Their key research areas include force/torque sensor calibration, sparse drift identification, and robot-environment interaction. Xu's most notable contribution is the development of the SDI (Sparse Drift Identification) approach, a novel methodology for calibrating force/torque sensors in industrial robots. This work, published in 2024, addresses critical challenges in maintaining sensor accuracy over time, offering a data-efficient solution that reduces calibration complexity while improving robustness. With 6 citations in its first year, the paper signals growing recognition of Xu's practical impact on manufacturing and automation. Xu's research bridges theoretical modeling and real-world application, providing tools that enhance robot performance in tasks like assembly and quality control. Their work is particularly valuable for students and engineers seeking to understand how sparse signal processing can optimize sensor systems in dynamic industrial environments.
Research Focus
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Top Papers
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