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About

Letizia Marchegiani is a robotics and autonomous systems researcher whose work spans energy-efficient robot navigation, multimodal perception, and human-robot collaboration. Her research is distinguished by a commitment to making autonomous systems more practical and deployable in real-world, often challenging environments. Marchegiani's early contributions focused on energy-aware robotics; her work on scheduled perception (26 citations) demonstrated how robots can intelligently switch between localisation subsystems to conserve energy, while a complementary framework leveraging publicly available maps further advanced predictive energy management. She has also pioneered unconventional sensing modalities, notably showing that auditory signals alone can provide reliable metric motion estimation and speaker localisation, opening new avenues for robust perception when vision fails. Her work on scene understanding for outdoor navigation (22 citations) addresses the limitations of category-based visual interpretation, reframing perception around robot-relevant concepts like driveability. The Oxford Offroad Radar Dataset (13 citations) reflects her commitment to advancing radar-based autonomy beyond urban settings. Additional contributions to human-robot search and rescue missions and agricultural vehicle connectivity underscore the breadth of her impact. With editorial leadership in active vision and human-robot collaboration, Marchegiani has established herself as a versatile and influential voice in modern robotics research.