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About

Federica Pascucci is an Italian robotics and autonomous systems researcher whose work has significantly advanced the field of mobile robot localization and navigation. Her research spans multi-robot systems, sensor fusion, outdoor and indoor positioning, and wireless sensor networks, with a particular focus on developing robust, decentralized algorithms for real-world deployment. Pascucci's most influential contribution is her development of the Interlaced Extended Kalman Filter (IEKF) for distributed multi-robot localization, a fully decentralized approach enabling teams of robots to dynamically correct and refine their positional estimates without centralized coordination — a landmark work that has accumulated over 511 citations. Her earlier research on GPS and inertial platform fusion for outdoor navigation (197 citations) established foundational methods for cost-effective mobile robot positioning in large-scale environments. Beyond classical robotics, Pascucci extended her expertise to emergency response applications, developing enhanced indoor positioning systems for first responders, and to wireless sensor networks through her Interlaced Extended Information Filter. Her algorithmic innovations also include evolutionary and genetic algorithm-based approaches to localization, broadening the toolkit available to researchers in this space. With a body of work combining theoretical rigor and practical application, Pascucci remains a key figure in autonomous navigation research.