Caroline Grand
Papers
2
Total Citations
16
H-Index
2
About
Caroline Grand is a pioneering researcher in developmental robotics and human-robot interaction, whose work focuses on endowing robots with the ability to learn and adapt autonomously through social and environmental feedback. Her key contributions center on two interrelated areas: self-assessment mechanisms for robot behavior and synchrony-based learning in social contexts. In her seminal 2013 paper, "How can a robot evaluate its own behavior? A neural model for self-assessment" (10 citations), Grand introduced a novel framework that allows robots to autonomously monitor and guide their own learning in unfamiliar environments, moving beyond pre-programmed strategies to genuine adaptive intelligence. Building on this foundation, her 2014 work, "Synchrony Detection as a Reinforcement Signal for Learning: Application to Human Robot Interaction" (6 citations), pioneered the use of temporal synchrony—the detection of rhythmic alignment between human and robot actions—as a natural reinforcement signal. This approach enables robots to initiate and sustain meaningful interactions with humans while simultaneously acquiring new competencies through social engagement. Grand’s research bridges cognitive science and robotics, offering elegant solutions to fundamental challenges in autonomous learning and intuitive human-robot collaboration.
Research Focus
Key Achievements
Top Papers
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