Papers

12

Total Citations

134

H-Index

6

About

G. Kanagaraj is a leading researcher in the intersection of robotics, optimization, and artificial intelligence, with a primary focus on solving complex inverse kinematics and assembly line balancing problems. His most impactful work, "Bio-inspired search algorithms to solve robotic assembly line balancing problems" (2015, 65 citations), established him as a key figure in applying nature-inspired metaheuristics to manufacturing efficiency. Kanagaraj has made significant contributions to inverse kinematics for redundant manipulators, developing hybrid algorithms like the e3GSA (Gravitational Search Algorithm) to enable precise path tracking under joint limits. His research extends to multi-robot systems, including reinforcement learning for swarm-robotics foraging tasks and Sandholm algorithm-based task allocation. Notably, his work on cost-efficient robotic assembly line design using non-dominated sorting genetic algorithms (2025) addresses real-world industrial challenges, while his charged system search algorithm for PCB drill path optimization (2015) demonstrates practical manufacturing applications. With a growing citation record and recent publications in autonomous vehicle logistics and disassembly line balancing, Kanagaraj continues to advance the field of intelligent robotics, making his research essential for students and engineers working on optimization-driven robotic systems.

Research Focus

Key Achievements

6
H-Index
12
Papers
134
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Bio-inspired search algorithms to solve robotic assembly line balancing problems
65 citations · 2015
📈 Most Prolific Year: 2015 (2 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Anna University, Chennai, Madurai Medical College, Monash University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago