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About

C. Balamurugan is a robotics researcher whose work has made significant contributions to the field of intelligent motion planning for industrial and autonomous robot manipulators. His research focuses primarily on evolutionary computation-based trajectory optimization, multi-objective optimization, and collision avoidance for robotic systems. Through the application of advanced evolutionary algorithms — notably the Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II), Multi-objective Differential Evolution (MODE), and Differential Evolution (DE) — Balamurugan has developed sophisticated methodologies for planning optimal robot trajectories in complex, obstacle-laden environments. His most impactful contributions include trajectory planning frameworks for the well-known PUMA 560 and Stanford robot manipulators, accounting for real-world constraints such as payload limitations and dynamic conditions. His 2008 paper on evolutionary multi-criteria trajectory modeling leads his citation record with 54 citations, while his broader body of work has collectively accumulated over 220 citations, reflecting meaningful influence within the robotics and computational intelligence communities. Notably, his introduction of Non-Uniform Rational B-Spline (NURBS)-based trajectory planning represents an innovative step toward more computationally refined motion planning for autonomous systems. His research continues to serve as a foundational reference for engineers and researchers working at the intersection of evolutionary optimization and robotic motion planning.