Papers
11
Total Citations
113
H-Index
6
About
Rahul Mangharam is a leading researcher at the intersection of cyber-physical systems, robotics, and control theory, with a focus on ensuring safety and reliability in autonomous systems. His work addresses fundamental challenges in real-time control, multi-agent coordination, and the simulation-to-reality gap. Mangharam pioneered the concept of "anytime computation and control," developing frameworks that co-design estimation accuracy and computational timing to meet stringent real-time requirements in safety-critical autonomous robots—a contribution recognized in his most-cited paper (31 citations). He has made significant advances in cooperative flight guidance for UAVs (17 citations) and temporal logic robustness for multi-agent mission planning (10 citations). His research on RecoNode (13 citations) introduced reconfigurable heterogeneous robots for search and rescue, while recent work on learning adaptive safety using Control Barrier Functions (2024) and bypassing the simulation-to-reality gap through online reinforcement learning (2023) demonstrates his continued impact. With over 100 publications and numerous awards, Mangharam also contributes to robotics education through modular hardware platforms, bridging theory and practice for students.
Research Focus
Key Achievements
Top Papers
- 1Co-design of Anytime Computation and Robust Control31 citations · 2015
- 2Cooperative Flight Guidance of Autonomous Unmanned Aerial Vehicles17 citations · 2011
- 3Anytime Computation and Control for Autonomous Systems14 citations · 2020
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- 5Temporal logic robustness for general signal classes10 citations · 2019
- 6Modeling Opportunities in mHealth Cyber-Physical Systems7 citations · 2017
- 7Learning Adaptive Safety for Multi-Agent Systems6 citations · 2024
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