Rahul Singhal

Malaviya National Institute of Technology Jaipur

Papers

Total Citations

H-Index

About

Rahul Singhal is a researcher whose work lies at the intersection of autonomous systems, path planning, and algorithmic optimization. His most cited contribution, "Shortest Path Evaluation with Enhanced Linear Graph and Dijkstra Algorithm" (2020), addresses a critical challenge in intelligent robotics: efficient navigation for autonomous vehicles. By refining the classic Dijkstra algorithm with enhanced linear graph structures, Singhal has advanced the practical deployment of robots in industrial and commercial settings where human intervention must be minimized. This work has garnered 8 citations, reflecting its relevance to the growing field of autonomous navigation. Singhal’s research is particularly significant for its focus on real-world applicability, bridging theoretical graph theory with the operational demands of autonomous systems. His contributions support the development of safer, more reliable autonomous vehicles, from warehouse robots to self-driving cars. For students and researchers exploring path planning or intelligent control, Singhal’s work offers a clear example of how foundational algorithms can be adapted to meet modern engineering challenges, making him a notable voice in the evolution of autonomous technology.