Hossein Abdi
Papers
4
Total Citations
38
H-Index
3
About
Hossein Abdi is a robotics researcher whose work sits at the intersection of safe autonomous navigation and microrobotics. His primary contributions focus on developing mathematically rigorous control frameworks that enable robots to operate safely in unknown and dynamic environments. Abdi is best known for pioneering Vision-based Control Barrier Functions (V-CBF), a novel approach that integrates real-time visual data with Control Barrier Function (CBF) theory to guarantee safe motion planning without requiring pre-mapped environments. His 2023 paper on this topic has already garnered 22 citations, reflecting its significance in the safety-critical robotics community. In related work, he has applied Control Lyapunov and Barrier Functions to achieve reactive, obstacle-aware path following for differential drive robots. Beyond terrestrial robotics, Abdi has explored the challenging domain of microrobotics, using reinforcement learning to enable self-learning swimming in viscous, stochastic environments and developing optimal control strategies for energy-efficient micro-swimmers at low Reynolds numbers. His research bridges theoretical control theory with practical deployment, addressing fundamental challenges in both macro-scale autonomous systems and micro-scale medical and manufacturing robots.
Research Focus
Key Achievements
Top Papers
- 1Safe Control using Vision-based Control Barrier Function (V-CBF)22 citations · 2023
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