Paulo Merloti

Papers

Total Citations

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About

Paulo Merloti is a robotics researcher whose work centers on vision-based autonomous navigation, with a particular focus on enabling robots to reliably follow a person in dynamic, real-world environments. His key research areas include computer vision, human-robot interaction, and adaptive sensor control. Merloti’s major contribution lies in addressing the critical challenge of maintaining robust person-tracking under extreme lighting variations—such as moving from direct sunlight into deep shade—and during complex, unpredictable human maneuvers like sharp turns or sudden sidesteps. His most cited paper (2010, 10 citations) introduces a system that achieves this through specialized image processing, while his earlier foundational work (2008, 5 citations) pioneered the use of real-time control of camera parameters—gain, shutter speed, and iris—to dynamically adapt to changing light conditions. Though his citation counts are modest, these papers represent important early steps in making robotic person-following practical for both indoor and outdoor settings. Merloti’s work is particularly notable for its emphasis on real-world robustness, addressing problems that remain central to the development of service robots, autonomous guides, and assistive technologies.