Papers
6
Total Citations
104
H-Index
4
About
Nicolas Drougard is a leading researcher at the intersection of physiological computing and human-robot interaction (HRI), pioneering adaptive systems that respond to the operator’s cognitive state. His work addresses a critical gap in automation: while machines grow increasingly capable, the human operator’s mental workload, stress, and fatigue remain largely ignored. Drougard’s key contributions center on **mixed-initiative human-robot teaming**, where tasks and authority are dynamically reallocated based on real-time estimates of the human’s current abilities. By fusing physiological sensors (e.g., heart rate, skin conductance) with behavioral data, he has developed discriminative features that predict operator performance, enabling systems to proactively adjust their autonomy. His most-cited paper, “How Can Physiological Computing Benefit HRI?” (52 citations), lays the conceptual foundation for this paradigm. Drougard has also advanced formal decision-making frameworks, such as **qualitative possibilistic MDPs**, to handle the inherent imprecision in human state estimation. Through his research, Drougard is shaping a future where human-automation teams are not just efficient, but truly collaborative—sensing and adapting to the human’s needs to optimize safety and mission success.
Research Focus
Key Achievements
Top Papers
- 1How Can Physiological Computing Benefit Human-Robot Interaction?52 citations · 2020
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- 4Human-Agent Interaction Model Learning based on Crowdsourcing6 citations · 2018
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- 6Qualitative Possibilistic Mixed-Observable MDPs3 citations · 2013