Rajdev Tiwari

JRE Group of Institutions, Jaypee Institute of Information Technology

Papers

Total Citations

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About

Rajdev Tiwari is a researcher specializing in autonomous robotics, path planning, and metaheuristic optimization algorithms. His work focuses on solving one of robotics' most fundamental challenges: enabling autonomous robots to efficiently navigate complex environments by identifying optimal paths between source and destination points, accounting for power requirements and environmental constraints. Tiwari's most significant contribution is his development of a modified Grey Wolf Optimization (GWO) approach for robotic path planning, published in 2021 and accumulating 50 citations — a testament to its resonance within the robotics and artificial intelligence communities. This work advances the practical deployment of autonomous robots by improving upon existing optimization frameworks to deliver more feasible and efficient navigation solutions. His 2020 comparative study of metaheuristic algorithms further establishes his expertise, systematically evaluating GWO alongside competing approaches to provide researchers with clearer guidance on algorithm selection for discrete optimization problems. With 17 citations, this work has become a useful reference for those benchmarking intelligent search strategies in robotics. Together, Tiwari's research offers meaningful advancements to the field of intelligent autonomous systems, making him a notable contributor to the growing intersection of swarm intelligence and robotic navigation.