Papers
8
Total Citations
80
H-Index
6
About
Magali Barbier is a leading researcher in autonomous multi-robot systems, specializing in distributed decision-making, hybrid planning, and robust plan execution under uncertainty. Her work addresses the critical challenge of enabling heterogeneous robot teams to cooperate effectively in dynamic, communication-constrained environments. Barbier’s most influential contribution is the HiDDeN architecture, a high-level distributed framework for cooperative plan execution and repair that allows robots to adapt to disruptions like communication losses and task delays. She has also pioneered hybrid planning algorithms that combine partial-order and hierarchical planning for real-time plan reparation, as demonstrated in her 2015 and 2019 papers. Her research extends to maritime autonomous vehicles, where she developed a generic, modular architecture for supervising behavior and reacting to environmental perturbations. With over 80 citations across her top papers, Barbier’s impact is evident in her consistent focus on integrating planning, execution, and repair into practical, scalable systems. Notably, her 2022 work on a hierarchical deliberative architecture based on goal decomposition provides a foundational framework for complex multi-robot missions, solidifying her reputation as a key innovator in autonomous robotics.
Research Focus
Key Achievements
Top Papers
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- 4A generic and modular architecture for maritime autonomous vehicles8 citations · 2018
- 5
- 6Using hybrid planning for plan reparation6 citations · 2015
- 7
- 8Knowledge Base for Planning, Execution and Plan Repair2 citations · 2012