Souad Hadjres

Papers

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About

Souad Hadjres is a pioneering researcher in autonomous robotics and topological mapping, whose work has fundamentally shaped how machines explore and understand unknown environments. Her primary research areas include graph-based world representation, non-metric exploration, and autonomous agent navigation. Hadjres’s major contribution lies in developing techniques that allow mobile robots to construct maps of unfamiliar spaces using only local information, without relying on precise positional data—a critical innovation for real-world applications where GPS or odometry may be unreliable. Her seminal 1993 paper, “Using Local Information in a Non-Local Way for Mapping Graph-Like Worlds” (45 citations), introduced a method for agents to explore and create topological maps by treating environments as graphs of discrete locations. This work was further refined in her 1996 studies (totaling 40 citations), which formalized exploration strategies in the absence of metric information. Hadjres’s research has been highly influential in the fields of robotics, artificial intelligence, and spatial cognition, providing foundational algorithms for autonomous systems operating in complex, unstructured settings. Her achievements continue to inspire students and researchers working on intelligent navigation and mapping.