Beena Gairola

University of Petroleum and Energy Studies

Papers

Total Citations

H-Index

About

Beena Gairola is a robotics researcher whose work focuses on advancing the precision and reliability of mobile robot localization, a fundamental challenge in autonomous navigation. Her most cited paper, "Investigation on optimized relative localization of a mobile robot using regression analysis" (2016, 3 citations), addresses the critical issue of odometry—the process of estimating a robot's position relative to its starting point using kinematic parameters. In this work, Gairola introduces a regression-based optimization method for differential drive wheel robots, improving the accuracy of relative localization by refining the identification of key kinematic parameters. This contribution is particularly valuable for applications in versatile mechanical autonomy, where robust self-localization is essential for tasks like mapping, path planning, and obstacle avoidance. While her citation count reflects the specialized nature of her research, Gairola’s work provides a practical, data-driven approach to a persistent problem in mobile robotics, offering a foundation for further advancements in autonomous systems. Her investigation underscores the importance of optimizing sensor data and kinematic models to enhance robot performance in real-world environments.