Papers
9
Total Citations
45
H-Index
4
About
Subhradip Mukherjee is a leading researcher in autonomous robotics, specializing in intelligent path navigation and obstacle avoidance for wheeled robots operating in challenging and unknown environments. His work centers on developing novel meta-heuristic algorithms—including the Obstacle-Avoiding Intelligent Algorithm (OAIA), Improved Particle Swarm Optimization (IPSO), and the Smart Algorithm for Wheeled Obstacle Avoidance (SAWOA)—that dramatically improve robot efficiency by minimizing path distance and elapsed time. With over 45 total citations across his most-cited papers, Mukherjee’s contributions have advanced both theoretical optimization and practical hardware implementation, integrating GPS, ZigBee, and ARM processors into functional prototypes. Notably, his 2020 paper on OAIA for quad wheel robots (11 citations) and his 2021 IPSO technique (8 citations) are foundational works in autonomous vehicle path planning. His recent research extends into life-saving applications, such as landmine detection robots (2024) and intelligent controllers for autonomous farming (2025), demonstrating a commitment to solving real-world challenges. Mukherjee’s hybrid controllers and predictive mechanisms continue to shape the future of mobile robotics.
Research Focus
Key Achievements
Top Papers
- 1Obstacle-avoiding intelligent algorithm for quad wheel robot path navigation11 citations · 2020
- 2A novel IPSO technique for path navigation and obstacle avoidance8 citations · 2021
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- 5An Experimental Study of a Landmine Detection Robot4 citations · 2024
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