Papers
1
Total Citations
9
H-Index
1
About
Shikha Jain is a researcher whose work centers on sensor fusion and autonomous mobile robotics, with a particular focus on improving position estimation—a critical challenge for reliable robot navigation. Her most-cited paper, "Application of Particle Filtering Technique for sensor fusion in mobile robotics" (2011), addresses the limitations of traditional Extended Kalman Filters (EKF) in handling non-linearities and non-Gaussian noise. By proposing a particle filtering approach for fusing data from multiple low-cost sensors, Jain demonstrated a more robust method for accurate pose estimation, directly impacting the development of cost-effective autonomous systems. While her citation count (9) reflects a focused, early-career contribution, the work is notable for tackling a foundational problem in mobile robotics: achieving high precision without expensive hardware. Jain’s research bridges theoretical filtering techniques with practical robotic applications, offering a valuable alternative to EKF-based methods. Her contribution is particularly relevant for researchers exploring sensor fusion in resource-constrained environments, where computational efficiency and accuracy must be balanced.
Research Focus
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Top Papers
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