Alessandro Saetti

Papers

Total Citations

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About

Alessandro Saetti is an emerging researcher working at the intersection of artificial intelligence, autonomous robotics, and symbolic planning. His work focuses on enabling robotic agents to operate intelligently within unknown or partially observable environments — a fundamental challenge in building truly autonomous systems. Saetti's most notable contribution centers on the problem of **online grounding of symbolic planning domains**, where he investigates how robots can dynamically map abstract, symbolic representations of tasks onto the real-world environments they inhabit. Rather than assuming prior environmental knowledge, his approach allows agents to explore, discover, and adapt their understanding incrementally — a significant step toward more flexible and deployable robotic systems. His research, published across 2021 and 2022, has already begun attracting attention from the robotics and AI planning communities, accumulating citations that reflect growing interest in bridging the gap between high-level symbolic reasoning and low-level sensorimotor interaction. While still early in his research career, Saetti addresses one of the field's most pressing open problems: making AI planning robust in the messy, unstructured settings of the real world. His work is particularly relevant for students and researchers interested in autonomous agents, task planning, and human-robot interaction.