Susmit Sanyal
Papers
1
Total Citations
3
H-Index
1
About
Susmit Sanyal is a researcher whose work lies at the intersection of computational intelligence, robotics, and decision-making under uncertainty. His primary contributions focus on advancing Type-2 fuzzy logic systems to enhance autonomous navigation in dynamic environments. In his most cited paper, "General Type-2 Fuzzy Reasoning for Path-Planning of a Mobile Robot in a Dynamic Environment under Sensory Uncertainty" (2024), Sanyal addresses a critical challenge: how robots can make reliable decisions when sensor data is imprecise or conflicting. By leveraging Type-2 fuzzy sets—which capture uncertainty not just in sensor readings but also in the membership functions themselves—he enables mobile robots to adapt more robustly to changing surroundings. This work has already garnered early attention with 3 citations, signaling its relevance to the growing field of intelligent robotics. Sanyal’s research bridges theoretical fuzzy logic with practical robotic applications, offering a framework that reduces the need for expert-tuned parameters while improving path-planning performance. His contributions are particularly valuable for students and engineers working on autonomous systems in unpredictable real-world settings, where traditional crisp logic often falls short.
Research Focus
Key Achievements
Top Papers
- 1