Narayan Panigrahi
Papers
1
Total Citations
3
H-Index
1
About
Narayan Panigrahi is a researcher whose work lies at the intersection of autonomous robotics and computer vision, with a particular focus on enabling mobile robots to navigate unstructured, off-road environments. His most cited contribution, the 2021 paper "Dual Segmentation Technique for Road Extraction on Unstructured Roads for Autonomous Mobile Robots," introduces a novel approach that combines semantic and instance segmentation to reliably identify traversable paths in challenging terrains—such as dirt tracks or forest trails—where traditional lane markings are absent. This work, which has garnered 3 citations, addresses a critical gap in autonomous navigation, offering a robust solution for agricultural, rescue, and exploration robots. Panigrahi’s research is notable for its practical emphasis on real-world deployment, bridging the gap between theoretical segmentation models and field-ready systems. His contributions are particularly valuable for students and engineers working on low-cost, vision-based autonomy, as his methods prioritize computational efficiency without sacrificing accuracy. Through this focused line of inquiry, Panigrahi is helping to pave the way for more versatile and resilient autonomous systems capable of operating beyond structured roads.
Research Focus
Key Achievements
Top Papers
- 1