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About

Fabio Pasqualetti is a prominent researcher whose work spans multi-agent systems, cooperative robotics, network security, and autonomous navigation. He is perhaps best known for his foundational contributions to the field of cooperative patrolling, where his rigorous mathematical frameworks for designing optimal multi-agent trajectories have become essential references for researchers in autonomous systems. His 2012 paper on cooperative patrolling, with nearly 200 citations, established key complexity results and approximation algorithms for coordinating teams of robots to efficiently monitor environments—work complemented by his analysis of weighted tour strategies for prioritized surveillance targets. Beyond robotics coordination, Pasqualetti has made significant contributions to secure networked systems. His early work on distributed intrusion detection for consensus networks—accumulating nearly 100 citations—addressed the critical challenge of identifying misbehaving nodes in multi-agent computations, a problem with deep implications for cyber-physical security. This security thread continued into his later research on spoofing-resilient trajectory planning and adversarial robot navigation, reflecting a sustained commitment to making autonomous systems robust against malicious attacks. More recently, Pasqualetti has explored bio-inspired coordination strategies, introducing time-inverted Kuramoto dynamics for persistent monitoring tasks. His body of work collectively advances both the theoretical foundations and practical deployment of resilient, intelligent multi-robot systems.