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About

Krittin Pachtrachai is a robotics and computer vision researcher whose work has made significant contributions to the field of surgical robotics, with a particular focus on hand-eye calibration for minimally invasive surgical systems. His research addresses one of the fundamental challenges in robot-assisted surgery: accurately determining the geometric relationship between a robot arm and its attached camera, a prerequisite for precise, image-guided interventions. Pachtrachai has consistently pushed the boundaries of conventional calibration approaches. His 2016 paper on calibration-object-free hand-eye calibration (46 citations) demonstrated that reliable transformations could be estimated without traditional reference targets, simplifying clinical workflows considerably. Building on this, his adjoint transformation algorithm (2018, 41 citations) advanced closed-form and iterative refinement methods, while his remote centre of motion work (2019, 26 citations) tackled constraints unique to laparoscopic robot configurations. His 2021 machine learning-based approach further modernized the field by eliminating dependence on calibration grids entirely. Collectively, his papers have accumulated over 140 citations, reflecting a sustained and meaningful impact on surgical robotics research. His body of work offers both theoretical rigor and practical relevance for researchers and engineers developing next-generation robotic surgical platforms.