Giulio Trigatti
Papers
2
Total Citations
85
H-Index
2
About
Giulio Trigatti is a robotics researcher specializing in trajectory planning for industrial spray painting applications. His work focuses on developing efficient, path-constrained algorithms that enable robots to achieve optimal coating quality while minimizing waste and cycle time. Trigatti’s most influential contribution is a novel trajectory planning strategy that accounts for the complex kinematics of spray painting robots, particularly those with non-spherical wrists. His 2018 paper on this topic has garnered 60 citations, reflecting its significance in advancing automation in manufacturing. In a related study, he introduced a look-ahead algorithm that further improves motion smoothness and precision, earning 25 citations. Trigatti’s research bridges the gap between theoretical robotics and practical industrial needs, offering solutions that enhance productivity and consistency in painting processes. His work is essential reading for engineers and researchers developing autonomous systems for surface coating, and his algorithms are increasingly referenced in the design of next-generation robotic painters.
Research Focus
Key Achievements
Top Papers
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