Dinesh Kumar Singh
Papers
2
Total Citations
29
H-Index
2
About
Dinesh Kumar Singh is a researcher whose work sits at the dynamic intersection of robotics, artificial intelligence, and computational intelligence. His research focuses primarily on multi-robotic navigation systems, path planning, and the integration of advanced AI methodologies to enhance autonomous robot performance in complex, variable environments. Singh's most notable contribution centers on developing hybrid frameworks that combine neural networks, fuzzy logic, and bio-inspired optimization techniques to address the challenging problem of multi-robot path planning. This interdisciplinary approach reflects a sophisticated understanding that no single AI paradigm sufficiently solves the intricate demands of real-world robotic navigation. By synthesizing these complementary methodologies, his work advances the reliability and adaptability of mobile robot systems across diverse industrial applications. His 2022 paper on this hybrid multi-robotic navigation approach has garnered 22 citations, demonstrating meaningful uptake within the robotics and computational intelligence communities. The work has attracted attention for its practical relevance in industries increasingly dependent on autonomous robotic systems for routine and hazardous task automation. For students and researchers entering the fields of autonomous robotics or swarm intelligence, Singh's work offers valuable foundational insights into how hybrid AI architectures can meaningfully improve navigation efficiency and decision-making in multi-agent robotic environments.
Research Focus
Key Achievements
Top Papers
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- 2