Somen Debnath

Papers

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About

Somen Debnath is a researcher whose work centers on intelligent systems, autonomous robotics, and computational intelligence, with a particular focus on mobile robot navigation and path planning. His research explores the integration of bio-inspired and soft computing techniques — including artificial neural networks (ANN), fuzzy logic, and genetic algorithms — to address complex real-world navigation challenges faced by autonomous mobile robots. Debnath's most recognized contribution, "Path Planning of Mobile Robot with Neuro-Genetic-Fuzzy Technique in Static Environment" (2014), has garnered 17 citations and demonstrates his innovative hybrid approach to robot path optimization. By combining the learning capabilities of ANN with the adaptive reasoning of fuzzy logic and the evolutionary search power of genetic algorithms, he developed a robust framework enabling mobile robots to intelligently select optimal paths while avoiding obstacles. His earlier work, "Path Planning of Mobile Robot with Neuro-Fuzzy Technique" (2012), laid the conceptual groundwork for this hybrid methodology, accumulating 6 citations and establishing his progressive research trajectory. Debnath's contributions are particularly valuable for students and researchers exploring autonomous systems, human-machine intelligence, and AI-driven robotics, offering practical frameworks that bridge theoretical computing paradigms with real-world engineering applications.