Deeptha Damodaran
Papers
1
Total Citations
16
H-Index
1
About
Deeptha Damodaran is a robotics researcher whose work focuses on the critical challenge of sensor perception for autonomous navigation, particularly in complex, human-centric environments. Her primary research areas include LiDAR-based robot localization, object detection, and the behavioral analysis of reflective surfaces. Her most notable contribution is the experimental analysis of how mirror-like objects—such as glass walls and polished metal—disrupt LiDAR-based navigation systems. In her highly cited 2023 paper, she systematically characterized the failure modes of LiDAR when encountering specular surfaces, demonstrating how these objects cause false positives, ghost targets, and localization drift. This work, which has garnered 16 citations, is foundational for developing more robust perception algorithms for mobile robots operating in modern indoor spaces like offices, malls, and hospitals. By identifying the specific behavioral patterns of reflective objects, Damodaran’s research provides a crucial stepping stone toward safer and more reliable autonomous navigation in environments where traditional sensor assumptions break down. Her findings are directly applicable to improving the resilience of service robots and autonomous vehicles.
Research Focus
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Top Papers
- 1