Prabir Kumar Jena
Papers
7
Total Citations
284
H-Index
6
About
Prabir Kumar Jena is a prominent researcher specializing in robotics, swarm intelligence, and autonomous navigation systems, with a particular focus on multi-robot path planning in complex and dynamic environments. His work sits at the intersection of computational intelligence and robotics, where he has made significant contributions by adapting and improving nature-inspired optimization algorithms to solve challenging real-world navigation problems. Jena's most impactful contribution is his 2020 paper on multi-robot path planning using an improved Particle Swarm Optimization algorithm with novel evolutionary operators, which has garnered over 160 citations and established him as a leading voice in the field. His earlier 2016 work introduced an Improved Gravitational Search Algorithm (IGSA) that ingeniously hybridized memory-based learning with social and cognitive factors from PSO, accumulating 57 citations. He has further broadened his algorithmic portfolio through hybrid approaches, including the IWD-DE framework and Improved Krill Herd algorithm, demonstrating a sustained commitment to cooperative multi-robot navigation in unknown environments. His foundational exploration of real-time A* algorithms and fuzzy logic controllers underscores a career built progressively on combining classical planning methods with intelligent adaptive techniques, making his research highly relevant to students and practitioners advancing autonomous robotic systems.
Research Focus
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Top Papers
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