Raghav Narula
Papers
1
Total Citations
12
H-Index
1
About
Raghav Narula is a researcher at the intersection of computer vision, robotics, and deep learning, with a focus on enabling autonomous systems to operate intelligently under severe resource constraints. His most cited work, "Efficient deep learning-based semantic mapping approach using monocular vision for resource-limited mobile robots" (2022, 12 citations), introduces a novel framework that allows mobile robots to build semantically rich maps of their environment using only a single camera and lightweight neural networks. This contribution is critical for real-world deployment, where computational power, memory, and energy are limited. Narula’s approach not only reduces hardware demands but also maintains high accuracy in scene understanding, paving the way for affordable, scalable robotic navigation in dynamic settings. By bridging the gap between state-of-the-art deep learning and practical embedded systems, his research has immediate implications for service robots, autonomous drones, and assistive technologies. With a growing citation record, Narula is establishing himself as a key voice in efficient, vision-based robotics, and his work continues to inspire new directions in low-power AI for mobile platforms.
Research Focus
Key Achievements
Top Papers
- 1