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K. Eguchi is a pioneering researcher in robotic welding automation, with a focus on intelligent sensing and real-time control of weld pool dynamics. His core contributions lie in developing advanced visual sensing systems and digital control strategies for multi-layer, one-side welding processes—critical for achieving high-quality joints in narrow-gap applications. Eguchi’s most cited work (2002, 8 citations) introduces a visual welding robot that senses and digitally controls the weld pool, emphasizing the importance of stable back bead formation in the first layer. He further innovated with the “switch back welding method” (2002, 3 citations), which coordinates current-waveform and torch motion to adapt to changing gap and welding position, enabling robust back bead control. His application of neural networks (2002, 2 citations) to detect arc length, extension length, and root gap represents an early integration of machine learning into welding process monitoring. Though his citation counts are modest, Eguchi’s work laid foundational techniques for automated, sensor-driven welding quality control, directly impacting industrial robotic welding efficiency and precision.