Papers
30
Total Citations
543
H-Index
13
About
Manoj Kumar Muni is a prominent robotics researcher whose work sits at the intersection of intelligent systems, path planning, and autonomous robot navigation. His research has made substantial contributions to two interconnected domains: humanoid robot navigation and mobile robot path optimization, with a particular emphasis on developing hybrid computational intelligence techniques. Muni's most influential work focuses on equipping robots with the ability to navigate complex, obstacle-laden environments efficiently. His 2018 study on fuzzy logic-based navigation for humanoid robots has garnered 82 citations, establishing him as a leading voice in intelligent humanoid control. Subsequent research on the NAO humanoid robot, bacterial foraging optimization, neural networks, and PID controllers further demonstrates his commitment to advancing motion planning methodologies. A defining hallmark of Muni's research philosophy is algorithmic hybridization — combining techniques such as fuzzy logic with genetic algorithms, whale optimization, sine-cosine algorithms with ant colony optimization, and intelligent water drops with genetic algorithms to achieve superior path-planning performance in both static and dynamic terrains. His ten most-cited papers collectively represent over 370 citations, reflecting substantial influence within the robotics and computational intelligence communities. His body of work offers valuable frameworks for researchers and engineers seeking robust, adaptive solutions for real-world autonomous robot deployment.
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