Vikas Kumar

National Institute of Technology Rourkela

Papers

Total Citations

H-Index

About

Vikas Kumar is a researcher specializing in autonomous navigation, multi-robot systems, and computational intelligence, with a particular focus on humanoid robotics. His work sits at the intersection of metaheuristic optimization and machine learning, where he develops innovative hybrid control frameworks designed to enhance the decision-making capabilities of robotic systems in complex environments. Kumar's most notable contribution involves the development of a hybrid navigational controller for multi-humanoid systems, achieved by integrating Moth–Flame Optimization (MFO) with reinforcement learning techniques. This pioneering approach addresses critical challenges in robotic navigation, specifically optimizing path length and minimizing traversal time — two fundamental concerns in real-world robotic deployment. By combining the exploratory power of metaheuristic algorithms with the adaptive learning capacity of reinforcement learning, Kumar's framework demonstrates a sophisticated understanding of both computational efficiency and practical robotics engineering. Though still building his citation record, with his 2022 navigation study already accumulating 10 citations, Kumar represents an emerging voice in intelligent robotics research. His hybrid methodology offers promising implications for future applications in collaborative humanoid systems, autonomous vehicles, and smart manufacturing environments, positioning him as a researcher worth following in the evolving field of AI-driven robotics.