Nagarajan Pitchandi

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About

Nagarajan Pitchandi is a researcher specializing in vision-based robotic assembly, with a focus on precise pose estimation and camera calibration for industrial automation. His work addresses critical challenges in visual servoing, where robotic manipulators rely on sensor feedback to interact with dynamic environments. His most-cited paper, "Vision Based Pose Estimation of Multiple Peg-in-Hole for Robotic Assembly" (2017, 21 citations), introduces methods for accurately determining the position and orientation of multiple components during assembly tasks—a key step toward flexible, autonomous manufacturing. In his 2016 study on GA-based camera calibration (14 citations), Pitchandi employs genetic algorithms to optimize camera parameters, enabling more reliable vision-assisted robotic systems. More recently, he has explored uncertainty-aware pose estimation with Fibonacci outlier elimination (2019), pushing the boundaries of robustness in image-based localization. With over 35 citations across his core works, Pitchandi’s contributions are foundational for researchers and engineers developing high-precision robotic assembly lines, where even millimeter-level errors can disrupt production. His work bridges computer vision and robotics, offering practical solutions for real-world automation challenges.