Pooja Pooja

National Institute of Technology Arunachal Pradesh

Papers

Total Citations

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About

Pooja Pooja’s research lies at the intersection of robotics, artificial intelligence, and autonomous navigation, with a particular focus on enabling intelligent decision-making in unknown environments. Her most cited work, “A Q-Learning Strategy for Path Planning of Robots in Unknown Terrains” (2022), introduces a reinforcement learning approach that allows mobile robots to autonomously learn collision-free, shortest paths without prior knowledge of obstacles. This contribution addresses a fundamental challenge in robotics: real-time adaptation to dynamic, unstructured settings. By leveraging Q-Learning, Pooja demonstrates how robots can iteratively improve their navigation strategies through trial and error, reducing reliance on pre-mapped data. Though her citation count is currently modest, her work marks a promising step toward scalable, learning-based path planning—a critical component for applications in search-and-rescue, warehouse automation, and exploratory robotics. Her research underscores a growing trend toward integrating machine learning with classical robotics, offering a foundation for future advances in autonomous systems. As the field evolves, Pooja’s contributions are poised to gain recognition for their practical relevance in bridging AI and real-world navigation challenges.