Rajib Paul
Papers
1
Total Citations
17
H-Index
1
About
Dr. Rajib Paul is a leading researcher at the intersection of autonomous systems and artificial intelligence, with a primary focus on the control and navigation of Unmanned Aerial Vehicles (UAVs). His most cited work, "Evaluation of Reinforcement and Deep Learning Algorithms in Controlling Unmanned Aerial Vehicles" (2021, 17 citations), provides a critical comparative analysis of modern AI-driven control methods for quadrotor drones. This study systematically assesses how reinforcement learning and deep learning architectures can enhance autonomous flight, addressing key challenges in stability, adaptability, and real-time decision-making for both military and civilian applications. By bridging the gap between theoretical AI algorithms and practical UAV deployment, Dr. Paul’s contributions offer a foundational framework for developing more intelligent and self-sufficient drone systems. His research is particularly valuable for students and engineers seeking to understand the trade-offs between traditional control theory and emerging learning-based approaches. With a growing citation impact, Dr. Paul continues to shape the future of autonomous aerial robotics, making his work essential reading for those advancing UAV autonomy in complex, dynamic environments.
Research Focus
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Top Papers
- 1