Papers
2
Total Citations
24
H-Index
2
About
Ram Prasad Padhy is a researcher at the forefront of autonomous robotics and computer vision, with a focused expertise in monocular vision-based navigation for Unmanned Aerial Vehicles (UAVs). His work addresses a fundamental challenge in robotics: enabling drones to perceive 3D depth and navigate complex environments using only a single RGB camera, eliminating the need for expensive depth sensors. His most-cited paper, "Monocular Vision-aided Depth Measurement from RGB Images for Autonomous UAV Navigation" (2022), has garnered 22 citations and demonstrates how deep learning can achieve depth estimation on par with dedicated depth cameras. In earlier work, "Localization of Unmanned Aerial Vehicles in Corridor Environments using Deep Learning" (2019), he tackled the specific challenge of pose estimation in GPS-denied indoor spaces, proving that a static monocular camera alone can guide a UAV through tight corridors. Padhy’s contributions are critical for advancing low-cost, lightweight autonomous systems, with direct applications in search-and-rescue, infrastructure inspection, and drone delivery. His research sits at the intersection of robot vision and deep learning, pushing the boundaries of what is possible with minimal sensory hardware.
Research Focus
Key Achievements
Top Papers
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