Papers
24
Total Citations
673
H-Index
12
About
Mihir Kulkarni is a pioneering roboticist whose work pushes the boundaries of autonomous exploration in the world's most challenging environments. His primary research focuses on resilient autonomy for subterranean and GPS-denied settings, with key contributions in multi-modal SLAM, collision-tolerant aerial robotics, and teamed exploration using legged and aerial robots. Kulkarni was a core member of Team CERBERUS, which won the prestigious DARPA Subterranean Challenge finals in 2021—a competition designed to advance technologies for exploring underground tunnels, caves, and urban infrastructure. His most cited paper (225 citations) details the system-of-systems approach that secured this victory. He also led the development of the RMF-Owl, a collision-tolerant flying robot designed for resilient subterranean exploration, and the MIMOSA framework for multi-modal SLAM that maintains localization accuracy even when sensors degrade. His work on reinforcement learning for collision-free flight (2024, 20 citations) represents a cutting-edge fusion of deep learning and autonomous navigation. With over 500 total citations across his top papers, Kulkarni's research is defining how robots can operate reliably in the most extreme, perceptually-degraded environments on Earth.
Research Focus
Key Achievements
Top Papers
- 1CERBERUS in the DARPA Subterranean Challenge225 citations · 2022
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- 5Resilient Collision-tolerant Navigation in Confined Environments27 citations · 2021
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