J. Sam Jebakumar
Papers
1
Total Citations
4
H-Index
1
About
J. Sam Jebakumar is a researcher specializing in autonomous robotics, sensor fusion, and precise localization systems for outdoor environments. His most notable contribution is the development of an Extended Kalman Filter (EKF)-based approach for fusing GPS and odometer data, enabling robust and accurate robot localization in outdoor settings. This work, published in 2014, addresses the inherent limitations of each sensor—GPS suffers from signal loss or multipath errors, while odometers accumulate drift over time—by intelligently combining their strengths. The resulting system provides reliable position estimates critical for autonomous navigation in unknown terrains. With 4 citations, this foundational paper has informed subsequent research in sensor fusion for mobile robotics. Jebakumar’s work is particularly relevant for applications in field robotics, autonomous vehicles, and precision agriculture, where dependable localization is paramount. His research underscores the importance of integrating complementary sensing modalities to overcome individual sensor weaknesses, a principle widely adopted in modern robotics. For students and researchers exploring localization challenges, Jebakumar’s EKF-based fusion method offers a practical and effective solution for achieving high-precision outdoor robot positioning.
Research Focus
Key Achievements
Top Papers
- 1