J. Poornima
Papers
1
Total Citations
2
H-Index
1
About
J. Poornima is a robotics researcher whose work centers on advancing autonomous navigation through multi-sensor fusion and uncertainty quantification. Her primary research areas include indoor robot localization, sensor integration, and robust perception systems for mobile robots. Her most notable contribution is a novel framework for fusing infrastructure camera feeds with on-board sensors to achieve scalable and reliable indoor localization. By developing a method to quantify spatially-varying uncertainty in external-camera-based pose estimates, she addresses a critical challenge in real-world deployment—ensuring robots can operate safely even when external sensing is imperfect. Her work builds an observation model for cameras based on upper-bound uncertainty estimates, enabling more resilient navigation in complex indoor environments. While her 2023 paper has garnered 2 citations to date, its practical significance lies in bridging the gap between laboratory precision and industrial scalability. Poornima’s research is particularly valuable for logistics, warehouse automation, and healthcare robotics, where robust localization is essential. Her contributions highlight the importance of principled uncertainty handling in autonomous systems, making her a promising voice in the field of intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1