Jeevan Raajan
Papers
1
Total Citations
10
H-Index
1
About
Jeevan Raajan is a researcher at the forefront of intelligent robotics and autonomous navigation, with a primary focus on integrating deep reinforcement learning into real-time robotic systems. His most cited work, "Real Time Path Planning of Robot using Deep Reinforcement Learning" (2020, 10 citations), introduces a novel framework that enables robots to dynamically compute collision-free paths in fully mapped environments, effectively navigating both static and dynamic obstacles. This contribution is particularly significant for applications in warehouse automation, autonomous vehicles, and service robotics, where rapid, adaptive decision-making is critical. By training an agent to optimize path selection in real time, Raajan’s research bridges the gap between theoretical reinforcement learning algorithms and practical robotic control, demonstrating how AI can enhance operational efficiency and safety. His work has garnered attention for its pragmatic approach to a longstanding challenge in robotics—balancing computational speed with robust obstacle avoidance. Raajan’s achievements underscore his ability to translate complex machine learning concepts into deployable solutions, making him a notable figure in the growing field of intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1Real Time Path Planning of Robot using Deep Reinforcement Learning10 citations · 2020