Marina Paolanti
Papers
4
Total Citations
149
H-Index
4
About
Dr. Marina Paolanti is a leading researcher at the intersection of robotics, computer vision, and deep learning, with a primary focus on automating complex inspection and surveying tasks. Her major contributions lie in developing intelligent robotic systems that leverage visual and textual data analysis to solve real-world industrial challenges. She pioneered the use of mobile robots for retail surveying, creating systems that autonomously navigate stores, analyze shelf images, and detect inventory issues—a breakthrough that dramatically reduces manpower costs and improves customer satisfaction. Her work in this area has garnered significant attention, with two foundational papers each earning 54 citations. Dr. Paolanti has also advanced rail safety through the development of "Felix," the first robotic platform capable of simultaneously measuring switch dimensions, geometrical railway parameters, and detecting dangerous situations. This innovation enhances measurement consistency and operator safety. Her research on semantic 3D object maps for robotic retail inspection further demonstrates her commitment to creating practical, deployable AI solutions. Through her highly cited work, Dr. Paolanti has established herself as a key figure in applied deep learning for autonomous systems, bridging the gap between academic research and tangible industrial automation.
Research Focus
Key Achievements
Top Papers
- 1Robotic retail surveying by deep learning visual and textual data54 citations · 2019
- 2
- 3Robotic platform for deep change detection for rail safety and security27 citations · 2017
- 4Semantic 3D Object Maps for Everyday Robotic Retail Inspection14 citations · 2019