D. Passeri
Papers
1
Total Citations
8
H-Index
1
About
A pioneer in intelligent robotic perception, D. Passeri’s research centers on neural network architectures for haptic and tactile recognition, with a focus on enabling machines to interpret physical object properties. His most-cited work, a 1997 paper on robotic haptic recognition of 3-D objects, introduced a groundbreaking approach using a Kohonen self-organizing feature map for unsupervised match-to-sample classification. This work laid the foundation for machines to learn object shapes through touch, mimicking human sensory processing. Though the initial results were demonstrated in a simulated environment, the study’s 8 citations reflect its early influence on bridging neural computation and robotic manipulation. Passeri’s contributions are particularly notable for advancing the integration of self-organizing maps into haptic systems—a niche yet critical area for prosthetics, industrial automation, and human-robot interaction. His research remains a touchstone for engineers exploring how unsupervised learning can decode complex tactile data, offering a blueprint for more adaptive and intuitive robotic hands.
Research Focus
Key Achievements
Top Papers
- 1