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About

Chiranjibi Champatiray is a researcher advancing the field of robotic assembly and manufacturing automation. His work centers on optimizing assembly sequence planning—the critical process of determining the most efficient order to put together complex products. Champatiray’s major contribution is integrating practical, real-world uncertainties—such as tool variability and robotic grip precision—into assembly planning algorithms, moving beyond idealized virtual simulations. His most cited paper (2023, 12 citations) introduces an optimal robotic assembly sequence planning method using a tool-integrated assembly interference matrix, directly addressing the gap between theoretical plans and industrial applicability. A subsequent study (2023, 9 citations) further tackles tool uncertainties, while his 2024 work (5 citations) employs a hybrid class topper optimization algorithm to enhance both efficiency and accuracy in robotic task planning. Earlier, his analysis of material selection for robot soft fingers (2020, 4 citations) explored power grasping, laying groundwork for dexterous manipulation. By systematically incorporating tool-related constraints and uncertainties, Champatiray is helping to make robotic assembly sequences more practical, cost-effective, and ready for real-world factory floors.