Rucha Sawlekar
Papers
1
Total Citations
7
H-Index
1
About
Rucha Sawlekar is a researcher advancing multi-modal perception for autonomous systems in extreme environments. Her work focuses on fusing event cameras and LiDAR to enable robust human and object tracking under adverse lighting conditions—such as total darkness, high-contrast zones, and blinding light—that challenge conventional sensors. Her most cited paper, "Event Camera and LiDAR based Human Tracking for Adverse Lighting Conditions in Subterranean Environments" (2023), has already garnered 7 citations, underscoring its timely impact on subterranean (SubT) robotics and search-and-rescue operations. By leveraging the asynchronous, high-dynamic-range capabilities of event cameras alongside LiDAR’s spatial precision, Sawlekar’s fusion approach achieves fast, accurate detection where traditional RGB cameras fail. This work is critical for autonomous navigation in mines, tunnels, and disaster zones, pushing the boundaries of perception in unstructured, low-visibility settings. Sawlekar’s contributions are shaping the next generation of resilient robotic systems, making her a notable voice in the intersection of computer vision, sensor fusion, and field robotics.
Research Focus
Key Achievements
Top Papers
- 1