Antonio Alipaz-Dicke
Papers
1
Total Citations
2
H-Index
1
About
Antonio Alipaz-Dicke is a robotics researcher specializing in the dynamic modeling and parameter identification of industrial manipulators. His work focuses on advancing frequency-domain techniques to extract inertial parameters from robot speed-controlled systems, offering significant improvements in accuracy and robustness over traditional time-domain methods. His most-cited paper, "Frequency-based Identification Routine for the Inertial Parameters of an Industrial Robot" (2022), introduces a novel framework that leverages frequency response data to precisely estimate mass, center of mass, and inertia tensors—critical for high-performance control and simulation. While his citation count is still building, this foundational contribution has been recognized for its potential to streamline calibration in manufacturing and collaborative robotics. Alipaz-Dicke’s research bridges theoretical system identification with practical industrial applications, positioning him as an emerging voice in the field. His ongoing work aims to extend these methods to flexible-joint robots and real-time adaptive control, promising to enhance the efficiency and safety of next-generation automation systems.
Research Focus
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Top Papers
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