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Delphine Dufourd is a robotics researcher whose work focuses on the critical intersection of autonomous navigation and human-robot interaction, particularly for defense and reconnaissance applications. Her most influential contribution, "Combinatorial maps for simultaneous localization and map building (SLAM)" (2005, 9 citations), addresses a fundamental challenge in robotics: how to create efficient, scalable environment models for SLAM. By introducing combinatorial maps as a representation, Dufourd provided a novel approach to handling the complexity of real-time mapping and localization, a problem that continues to underpin modern autonomous systems. Beyond SLAM, Dufourd has made significant strides in robot control architectures, notably through her work on HARPIC, which enables flexible human-robot collaboration. Her papers on controlling reconnaissance robots (2004, 4 citations) and assessing autonomous functionalities (2007, 3 citations) demonstrate a systematic approach to balancing machine autonomy with human oversight in high-stakes military settings. Dufourd’s research is particularly notable for its practical focus: she addresses the real-world stress and cognitive load faced by operators, proposing architectures that allow seamless transitions between teleoperation and autonomous behavior. Her work remains relevant for researchers developing robust, human-aware robotic systems for complex environments.