Dipanjan Konar
Papers
2
Total Citations
6
H-Index
2
About
Dipanjan Konar is a researcher at the forefront of intelligent robotics and human-robot interaction, with a core focus on path planning under uncertainty and brain-computer interfacing. His work masterfully bridges the gap between computational intelligence and real-world robotic autonomy. Konar’s major contributions lie in developing robust navigation systems for mobile robots operating in dynamic, unpredictable environments. He pioneered the application of General Type-2 Fuzzy Logic to path planning, addressing sensory uncertainty by modeling membership functions as a union of multiple expert-defined Type-1 sets, thereby capturing higher-order vagueness that classical fuzzy systems cannot. This approach allows robots to make safer, more adaptive decisions when sensor data is noisy or conflicting. In parallel, Konar has explored the use of EEG signals for error correction in robotic path planning, integrating learning automata to enable robots to learn from human neural feedback in real time. Though his most cited works currently hold 3 citations each, they represent foundational steps in merging fuzzy reasoning with cognitive robotics. His research is particularly notable for its practical implications in assistive robotics and autonomous navigation, where reliability under uncertainty is paramount.
Research Focus
Key Achievements
Top Papers
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- 2