Marco Carletti

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About

Marco Carletti is a researcher in robotics and computer vision, focusing on active perception and 3D object recognition for autonomous agents. His key research areas include active object classification, multi-view deep learning, and scene understanding in cluttered environments. Carletti’s major contributions center on developing frameworks that enable robots to intelligently explore their surroundings, notably through his concept of "recognition self-awareness"—an intermediate reasoning layer that guides which views to prioritize during object exploration. This work, published in 2019, has garnered 9 citations and demonstrates how deep 3D classifiers can be trained to optimize viewpoint selection. In a related study (7 citations), he addressed the challenge of classifying multiple objects in cluttered scenes, proposing methods for robust perception in realistic, assistive robotics contexts. Carletti’s research bridges the gap between passive recognition and active decision-making, enhancing how autonomous systems interact with complex environments. His contributions are particularly relevant for applications in service robotics and human-robot interaction, where accurate, efficient object recognition is critical for safe and effective operation.