Papers
4
Total Citations
126
H-Index
4
About
Sunil Kumar is a robotics and autonomous systems researcher whose work centers on mobile robot path planning, optimization algorithms, and intelligent decision-making frameworks. His research addresses critical limitations in conventional path planning approaches — including inefficient routing, high collision risk, and poor adaptability in complex environments — by developing novel algorithmic solutions that push the boundaries of autonomous navigation. Kumar's most recognized contribution, "Optimum Mobile Robot Path Planning Using Improved Artificial Bee Colony Algorithm and Evolutionary Programming" (2022, 48 citations), demonstrates his expertise in applying bio-inspired metaheuristics to real-world robotics challenges. Complementing this, his node reduction-based probabilistic roadmap algorithm (42 citations) introduces a sophisticated decision-making strategy that significantly reduces path length and sampling inefficiencies that have long plagued traditional methods. His hybrid framework for single and multi-robot coordination in industrial environments (29 citations) further underscores his commitment to scalable, practical solutions. Collectively amassing over 126 citations within a single publication year, Kumar has rapidly established himself as a meaningful contributor to the field. His work is particularly valuable for researchers and engineers designing autonomous systems for complex, real-world industrial deployments, offering both theoretical rigor and applied relevance.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4