Rohan Kumar Manna
Papers
2
Total Citations
20
H-Index
2
About
Rohan Kumar Manna is pioneering the frontier of energy-efficient autonomous aerial navigation through bio-inspired neuromorphic vision systems. His research centers on integrating Dynamic Vision Sensors (DVS) and event-based cameras with physics-guided neural planners, fundamentally rethinking how drones perceive and navigate complex environments. Manna’s flagship work, “EV-Planner: Energy-Efficient Robot Navigation via Event-Based Physics-Guided Neuromorphic Planner” (2024), has already garnered 16 citations, demonstrating its immediate impact on the robotics community. In this paper, he introduces a novel framework that leverages the asynchronous, low-latency output of event cameras to dramatically reduce computational and energy demands compared to traditional frame-based approaches. His follow-up study (2025) further refines this paradigm, achieving robust obstacle avoidance with minimal power consumption. Manna’s contributions are particularly notable for bridging neuromorphic computing with practical aerial robotics, offering a scalable path toward long-endurance drones. By replacing conventional vision pipelines with physics-informed, event-driven processing, he addresses critical bottlenecks in autonomous navigation—speed, efficiency, and reliability. His work stands as a key reference for researchers exploring energy-constrained robotics, edge AI, and neuromorphic engineering.
Research Focus
Key Achievements
Top Papers
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- 2