Valquiria Fenelon

Centro Universitário FEI, Universidade de São Paulo

Papers

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About

Valquiria Fenelon is a pioneering researcher in the intersection of computer vision, cognitive science, and mobile robotics, with a distinctive focus on the informational value of shadows. Her work redefines how autonomous systems perceive and navigate their environments by leveraging qualitative spatial reasoning and occlusion-based cues. Fenelon’s key contributions include demonstrating that shadows—often overlooked in robotics—can serve as robust sources of localization data, mirroring the human visual system’s reliance on shadow information for depth perception. Her 2009 paper on qualitative robot localization using cast shadows (15 citations) and her 2012 work on reasoning about shadows in mobile robot environments (12 citations) laid foundational methods for probabilistic self-localization on qualitative maps, as further developed in her 2016 study (8 citations). By bridging cognitive psychology and robotics, Fenelon has advanced the field’s understanding of how spatial knowledge can be extracted from incomplete visual data, enabling robots to locate themselves and objects with minimal sensors. Her research remains influential for students and engineers working on low-cost, perception-driven autonomous systems, highlighting the untapped potential of everyday visual phenomena in artificial intelligence.