NK Shukla
Papers
2
Total Citations
12
H-Index
2
About
NK Shukla is a researcher specializing in autonomous robotics and computational intelligence, with a particular focus on multi-robot path planning in complex and unknown environments. Their work addresses one of the most pressing challenges in modern robotics: enabling robots to autonomously navigate intricate environments filled with static and dynamic obstacles while optimizing their movement efficiently. Shukla's most notable contributions center on the application of bio-inspired and swarm intelligence algorithms to solve path planning problems. Their 2019 study on Particle Swarm Optimization (PSO) for multi-robot path planning introduced a novel approach to establishing optimized navigation routes, garnering 8 citations and highlighting the significance of automation and detection capabilities in robotics. Complementing this work, Shukla also explored the Cuckoo Search (CS) Algorithm in combination with PSO, demonstrating the value of hybrid metaheuristic approaches for autonomous agents operating in uncertain environments, earning an additional 4 citations. Together, these contributions reflect Shukla's dedication to advancing intelligent robotic systems through optimization techniques. Their research provides valuable frameworks for students and engineers working on autonomous navigation, making meaningful strides toward more reliable and efficient robotic systems in real-world applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2