Sergio Angulo

Papers

Total Citations

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About

Sergio Angulo’s research lies at the intersection of robotic perception, active vision, and probabilistic modeling, with a focus on enabling autonomous systems to intelligently interact with their environments. His most cited work, "Task-Oriented Probabilistic Active Vision" (2010), introduces a pioneering framework where a robot’s visual attention is guided not by generic curiosity, but by the specific demands of its current task. By modeling uncertainty in the world and actively reducing only the most task-relevant components, Angulo’s approach bridges the gap between perception and action, allowing robots to allocate computational resources efficiently. Though his citation count remains modest—with this key paper garnering 4 citations—the conceptual clarity of his contribution has influenced subsequent work in active perception and decision-making under uncertainty. Angulo’s research underscores a shift from passive sensing to goal-driven exploration, a principle now central to modern robotics and autonomous navigation. His work is particularly valuable for students and researchers seeking to understand how probabilistic reasoning can make robotic vision both purposeful and computationally tractable.