Papers
9
Total Citations
135
H-Index
7
About
Faezeh Rahbar is a leading researcher in gas sensing mobile robotics, specializing in odor source localization, multi-robot systems, and human-robot interaction. Her major contributions include pioneering 3D bio-inspired algorithms for detecting airborne chemical sources, addressing the critical limitation of prior 2D approaches in realistic environments. Her work on the Infotaxis-based 3D algorithm and Adaptive Lévy Taxis has significantly improved robotic search efficiency in hazardous scenarios, with applications in search and rescue, environmental monitoring, and industrial safety. With over 135 citations across her most cited works, her 2017 paper on 3D bio-inspired odor source localization (37 citations) and her 2015 study on predicting extraversion from non-verbal features in human-robot interaction (20 citations) highlight her interdisciplinary impact. She has also advanced distributed source term estimation for multi-robot systems and data-driven plume modeling for built environments. Rahbar’s research bridges theoretical algorithms and practical validation, earning recognition for enhancing robotic autonomy in critical, real-world conditions. Her work continues to inspire innovations in autonomous sensing and collaborative robotics.
Research Focus
Key Achievements
Top Papers
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- 7A Distributed Source Term Estimation Algorithm for Multi-Robot Systems11 citations · 2020
- 8Information-Driven Gas Distribution Mapping for Autonomous Mobile Robots4 citations · 2023
- 9Source Term Estimation Algorithms for Gas Sensing Mobile Robots3 citations · 2021