Biswajit Sarkar
Papers
4
Total Citations
41
H-Index
3
About
Biswajit Sarkar’s research lies at the intersection of robotics, sensor-based mapping, and decision-making under uncertainty. His early work focuses on indoor environment mapping using laser range scanners, where he developed methods for extracting and merging line segments to build accurate spatial representations. His 2014 paper on this topic, with 21 citations, remains a foundational reference in autonomous navigation. He further advanced localization techniques by proposing a novel method for computing importance weights in Monte Carlo localization on line-segment maps (2015, 14 citations), improving robot pose estimation in structured environments. More recently, Sarkar has ventured into theoretical frameworks for multi-attribute decision-making, introducing q-rung logarithmic Pythagorean neutrosophic vague normal aggregating operators (2023). This work extends fuzzy set theory to handle complex, uncertain data—with applications in agricultural robotics. His earlier applied work includes online radiation mapping using mobile robots at a cyclotron facility (2011), demonstrating his ability to bridge theory with real-world safety challenges. With contributions spanning from practical SLAM algorithms to advanced aggregation operators, Sarkar’s research offers valuable tools for both robotic perception and intelligent decision systems.
Research Focus
Key Achievements
Top Papers
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