Patricia Lasserre
Papers
1
Total Citations
2
H-Index
1
About
Patricia Lasserre’s research lies at the intersection of robotics, advanced manufacturing, and artificial intelligence, with a particular focus on integrating machine learning into composite material production. Her most-cited work, "Robot-Assisted Composite Manufacturing Based on Machine Learning Applied to Multi-view Computer Vision" (2020), introduces a novel framework that combines multi-view computer vision with robotic systems to enhance precision and adaptability in composite layup processes. By leveraging deep learning algorithms to analyze visual data from multiple angles, Lasserre’s approach enables real-time defect detection and automated adjustments, significantly improving manufacturing efficiency and material quality. Although early in its citation impact—with 2 citations to date—this paper represents a pioneering step toward intelligent, data-driven fabrication in aerospace and automotive industries. Lasserre’s contributions are notable for bridging the gap between theoretical machine learning models and practical robotic applications, offering a scalable solution for complex, high-stakes manufacturing environments. Her work underscores a commitment to advancing Industry 4.0 paradigms, where adaptive automation and sensor fusion drive next-generation production systems.
Research Focus
Key Achievements
Top Papers
- 1