S. Venugopal

National Institute of Technology Nagaland

Papers

Total Citations

H-Index

About

S. Venugopal is a researcher whose work sits at the intersection of robotics, artificial intelligence, and industrial automation. His most recognized contributions center on the application of evolutionary computation techniques to solve complex real-world optimization problems, particularly in autonomous mobile systems. Venugopal's most impactful research focuses on mobile robot path planning, where he developed the Mobile Robot Path Search based on a Multi-Objective Genetic Algorithm (MRPS-MOGA), a novel framework designed to address the computational complexity inherent in navigating robots through dynamic industrial environments. This approach applies multi-objective genetic algorithms to simultaneously optimize competing criteria such as path length, safety, and efficiency — challenges that traditional single-objective methods struggle to resolve effectively. His 2022 publication on this topic has garnered 46 citations, reflecting strong uptake within the robotics and automation research community. Venugopal's work is particularly valuable to engineers and scientists seeking scalable, intelligent solutions for autonomous navigation in manufacturing and logistics settings. His contributions represent a meaningful step forward in making industrial automation more adaptive, cost-effective, and computationally feasible, establishing him as a notable voice in applied evolutionary robotics research.