K J Poornaselvan

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About

K. J. Poornaselvan is a researcher whose work sits at the intersection of artificial intelligence, robotics, and autonomous systems. His research focuses on intelligent path planning for mobile robots, with a particular emphasis on developing adaptive algorithms capable of operating under conditions of uncertainty. Poornaselvan's most notable contribution involves the application of Fuzzy Support Vector Machines (FSVM) within a multi-agent framework to solve complex optimal path planning challenges in robotic environments. This work addresses a critical limitation in traditional mobile robotics, where robots are constrained to predefined paths in known environments. By integrating fuzzy logic with support vector machine learning, his approach equips robots with enhanced sensing, learning, and reasoning capabilities, enabling more robust navigation in dynamic and unpredictable settings. His 2010 publications in this domain have garnered citations that reflect the foundational relevance of his contributions to the robotics and machine learning communities. For students and researchers exploring autonomous navigation, multi-agent systems, or hybrid AI methodologies, Poornaselvan's work offers a meaningful entry point into how intelligent algorithms can bridge the gap between theoretical AI models and real-world robotic applications.