Tanmoy Kumar Das
Papers
1
Total Citations
3
H-Index
1
About
Tanmoy Kumar Das is a robotics researcher specializing in sensor fusion, autonomous navigation, and intelligent control systems. His work addresses a critical challenge in unmanned robotics: maintaining precise localization even when individual sensors fail. In his most-cited paper, "Extended Kalman Filter based fusion of reliable sensors using fuzzy logic" (2017, 3 citations), Das pioneered a novel approach that integrates fuzzy logic with probabilistic algorithms to dynamically assess sensor reliability. This method ensures robust position estimation by filtering out faulty sensor data, significantly improving the performance of autonomous robots in real-world environments. Though early in his citation impact, Das's contribution is notable for bridging the gap between traditional Kalman filtering and adaptive intelligence, offering a practical solution for fault-tolerant navigation. His research holds promise for applications in autonomous vehicles, drones, and industrial robotics, where sensor failure can lead to catastrophic errors. Das continues to explore the intersection of fuzzy systems and probabilistic robotics, aiming to make autonomous systems more resilient and trustworthy.
Research Focus
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Top Papers
- 1