Alexandre Bucquet
Papers
1
Total Citations
11
H-Index
1
About
Alexandre Bucquet is a researcher at the forefront of human-robot interaction, with a particular focus on the complex dynamics of multi-agent teams. His work addresses a critical gap in the field: moving beyond single-human-robot models to understand how robots can effectively influence leadership and followership within human groups. His most-cited paper, “Influencing Leading and Following in Human-Robot Teams” (2019, 11 citations), introduces novel mathematical frameworks to capture the emergent behaviors that define group coordination—such as who leads and who follows. This contribution is foundational for designing robots that can seamlessly integrate into collaborative human teams, rather than merely interacting with individuals. Bucquet’s research has significant implications for fields ranging from search-and-rescue operations to collaborative manufacturing, where effective team dynamics are critical. By modeling these underlying social mechanics, his work paves the way for robots that can adaptively influence group behavior, making them more intuitive and effective partners in real-world team settings.
Research Focus
Key Achievements
Top Papers
- 1Influencing Leading and Following in Human-Robot Teams11 citations · 2019