V Gurunathan
Papers
1
Total Citations
3
H-Index
1
About
V Gurunathan is a rising researcher in the field of autonomous robotics, with a focused expertise in intelligent navigation systems and deep reinforcement learning. Their most-cited work, "Comprehensive Exploration of Enhanced Navigation Efficiency via Deep Reinforcement Learning Techniques" (2024), addresses a critical challenge in modern robotics: enabling mobile robots to navigate independently in uncertain, dynamic environments. This paper tackles the limitations of conventional navigation methods, which often fail when faced with moving objects and constantly changing terrain. By applying advanced reinforcement learning techniques, Gurunathan’s work offers a pathway to more adaptive and resilient robotic systems. While still early in their career, with 3 citations on this key paper, their contribution is already recognized as a valuable step toward robust, real-world autonomous navigation. Gurunathan’s research is particularly relevant for students and engineers working on mobile robotics, autonomous vehicles, and AI-driven control systems, promising to influence future developments in how machines perceive and move through complex, unpredictable spaces.
Research Focus
Key Achievements
Top Papers
- 1