Rajat Agrawal

Malaviya National Institute of Technology Jaipur

Papers

Total Citations

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About

Rajat Agrawal is a researcher focused on advancing autonomous navigation, with a particular emphasis on mobile robot path planning and optimization. His work addresses one of the most critical challenges in robotics: enabling robots to navigate complex environments efficiently and safely. Agrawal’s major contributions include a comprehensive review of classical path planning approaches, which has become a foundational reference for researchers and engineers in the field, garnering 5 citations since 2022. This review systematically evaluates traditional methods, providing clarity on their strengths and limitations in real-world applications. Additionally, Agrawal has pioneered novel algorithmic solutions, such as the Multi-Objective Adaptive Ant Colony Optimization (MO-AACO), which tackles the NP-hard nature of path planning by balancing multiple objectives like path length, safety, and energy efficiency. This work, with 2 citations, demonstrates his ability to blend bio-inspired computation with practical robotics challenges. Agrawal’s research is particularly notable for its focus on adaptive and multi-objective frameworks, offering scalable solutions for dynamic environments. His contributions are shaping the next generation of autonomous systems, making him a rising voice in intelligent robotics and optimization.