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About

Pooyan Fazli is a robotics and artificial intelligence researcher whose work centers on multi-robot coordination, autonomous navigation, and computer vision. He is best known for his foundational contributions to the multi-robot area coverage problem, which asks how teams of robots can efficiently and completely survey an environment—particularly under real-world constraints such as limited sensor range and the presence of obstacles. His 2013 paper on multi-robot repeated area coverage (62 citations) and his 2010 work on complete and robust cooperative coverage (52 citations) established influential algorithmic frameworks, including guard-placement strategies and cluster-based distributed methods, that remain key references in the field. Beyond coverage, Fazli has contributed to multi-robot task allocation with complex scheduling constraints, probabilistic local planning for safe navigation in cluttered and dynamic environments, and integrated robot vision systems—most notably the "Curious George" platform, which demonstrated near real-time object recognition using web-sourced training data. His participation in the Semantic Robot Vision Challenge further reflects his interest in bridging perception and autonomous behavior. Collectively, his body of work, accumulating nearly 220 citations, offers both theoretical grounding and practical solutions for deploying robot teams in complex, real-world settings.