Mohit Ranjan Panda
Siksha O Anusandhan University, Dr. C. V. Raman University, KIIT University
Papers
5
Total Citations
86
H-Index
4
About
Mohit Ranjan Panda is a robotics and computational intelligence researcher whose work sits at the intersection of bio-inspired optimization and autonomous systems. His primary research focus centers on multi-robot motion planning and path optimization, where he has made significant contributions by developing and hybridizing nature-inspired metaheuristic algorithms to solve complex navigation challenges in dynamic environments. Panda's most influential work involves the creative hybridization of established optimization techniques — most notably his pairing of Invasive Weed Optimization (IWO) with the Firefly Algorithm, which has garnered 39 citations, and his fusion of IWO with Improved Particle Swarm Optimization (IPSO) for multi-robot navigation, cited 27 times. These contributions address a critical gap identified in earlier metaheuristic approaches, which struggled with adaptability in complex, non-stationary environments. His 2016 work combining Particle Swarm Optimization with Tabu Search further demonstrates his commitment to hybrid methodologies that enhance robustness and efficiency in path planning. Across his published work, Panda consistently tackles real-world challenges such as minimizing path length, ensuring collision avoidance in cluttered environments, and achieving self-determination in autonomous systems. With over 85 cumulative citations, his research offers valuable frameworks for students and engineers developing next-generation autonomous mobile robotics solutions.
Research Focus
Key Achievements
Top Papers
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