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About

Giacomo Ziliani is a robotics and control systems researcher whose work centers on the intelligent automation of complex industrial manipulation tasks. His primary contributions lie in hybrid force/velocity control, iterative learning control (ILC), and mechatronic system design, with a particular focus on enabling industrial robots to interact adaptively with objects of unknown geometry. Ziliani's most influential work, "Iterative-Learning Hybrid Force/Velocity Control for Contour Tracking" (2010, 37 citations), demonstrates how ILC algorithms can significantly enhance a robot's ability to trace unknown contours — a capability far beyond traditional pre-programmed motion. This builds upon his earlier foundational research into velocity feedback in hybrid force/velocity control (2005, 29 citations) and friction compensation strategies (2006), which together address the practical challenges of achieving precise, stable contact during real-world tasks. A defining theme in Ziliani's career is robotic deburring — the automated removal of manufacturing imperfections — where his mechatronic design methodology (2007, 31 citations) has garnered substantial attention. By integrating mechanical, electronic, and control design considerations holistically, his approach has provided a practical framework for deploying adaptive robots in unstructured industrial environments, making his body of work highly relevant to researchers advancing flexible manufacturing automation.