Pasquale Franciosa
Papers
8
Total Citations
266
H-Index
6
About
Pasquale Franciosa is a leading researcher in intelligent manufacturing, specializing in in-line metrology, robotic inspection, and fault-tolerant control for Industry 4.0. His work bridges the gap between theoretical robotics and practical zero-defect manufacturing, with a focus on free-form surface inspection and compliant part handling. Franciosa’s most impactful contributions include developing coverage path planning algorithms with targeted viewpoint sampling for robotic 3D optical scanners, achieving 76 citations, and spatio-temporal adaptive sampling methods that reduce mean-time-to-detection of quality defects (61 citations). He has also advanced in-line dimensional inspection using Laser Radar systems for automotive assembly (47 citations) and pioneered fault diagnosis and fault-tolerant control for uncertain robot manipulators using high-order sliding mode techniques (43 citations). His research extends to multi-robot motion planning and trajectory optimization for handling compliant sheet metal parts in stamping lines, directly addressing industrial productivity and quality challenges. More recently, Franciosa has explored adaptive transfer learning for welding defect classification, demonstrating his commitment to integrating AI with manufacturing. With over 250 total citations, his work is essential reading for researchers and engineers seeking to implement robust, automated quality control systems in smart manufacturing environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8