Xindu Chen

Papers

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About

Xindu Chen is a researcher specializing in robotic machining, with a primary focus on grinding robots and five-axis milling operations. Their work addresses critical challenges in industrial automation, particularly the integration of 3D vision systems to enhance robot intelligence and precision. Chen’s most cited paper (2018, 29 citations) introduces a 3D vision system that enables grinding robots to automatically position and measure workpieces, overcoming economic and accuracy barriers that previously limited automation. This contribution directly improves machining efficiency and intelligence. Further work includes a calibration method for vision measurement systems on ceramic billet grinding robots (2019, 4 citations), which enhances machining accuracy through a two-step calibration process. Chen also tackles the complex optimization of functional redundancy in 6R robots for smoother five-axis milling (2023, 7 citations), addressing the nonlinear trade-off between motion smoothness and performance. These contributions demonstrate Chen’s impact on advancing robotic precision and autonomy in manufacturing, with applications in grinding and milling that push the boundaries of current industrial robotics.