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About

Ouahiba Azouaoui is a prominent robotics researcher whose work centers on autonomous mobile robot navigation, motion planning, and environment perception. With a career spanning over two decades, her contributions have significantly advanced the field of safe and intelligent robotic systems operating in complex, real-world environments. Azouaoui's most influential work addresses the critical challenge of navigating dynamic, unknown environments. Her 2014 paper on passively safe partial motion planning for robots with limited sensory fields-of-view (21 citations) established important safety guarantees for real-time navigation scenarios. Complementing this, her research on moving obstacle detection using laser range finders (20 citations) provided foundational perception capabilities essential for dynamic environments. Her contributions extend to optimization-driven approaches, including particle swarm optimization applied to scan-matching and safe motion planning tree expansion, as well as SLAM implementation for bi-steerable robots, demonstrating her breadth across perception, localization, and planning. Her work on HOG-based multi-object detection further bridges robotics with urban autonomous driving applications. Notably, her early exploration of autonomous robotic systems behavior and intelligence (1998) reveals a long-standing commitment to the field. With publications consistently attracting citations across multiple decades, Azouaoui has established herself as a sustained and impactful contributor to intelligent mobile robotics research.