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About

Mabaran Rajaraman is a leading researcher in robotic automation, specializing in intelligent manufacturing and industrial inspection. His work centers on developing computational frameworks that enable robots to autonomously perform complex tasks—such as surface inspection and welding—with minimal human intervention. Rajaraman’s major contributions include pioneering a novel approach that combines coverage planning with reinforcement learning to generate optimal inspection paths in real time, a breakthrough that has garnered 53 citations. He also advanced workpiece localization for robotic welding, eliminating the need for custom fixtures and significantly streamlining production workflows. His sampling-based motion planning method for redundant robotic systems, featuring a 7-DOF manipulator and turntable, has been cited 21 times and demonstrates his expertise in solving real-world industrial challenges. With over 100 total citations, Rajaraman’s research directly impacts factory productivity and cost reduction, making him a key figure in the evolution of smart manufacturing. His work is essential reading for students and engineers seeking to understand how robotics and machine learning converge to automate repetitive, high-precision tasks.