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About

Naoki Asakawa is a pioneering robotics and manufacturing automation researcher whose work has fundamentally advanced the application of industrial robots to complex surface-finishing and fabrication tasks. His research centers on robotic automation of traditionally skill-dependent manual processes, including spray-painting, polishing, chamfering, deburring, and metal forming — areas where human expertise has historically been difficult to systematize and replicate. Asakawa's most influential contributions lie in developing intelligent, teachingless control systems for six-degree-of-freedom industrial robots. His landmark 2002 paper on automated spray-painting of sculptured surfaces (74 citations) eliminated the need for skilled manual teaching, while his complementary work on collision-free polishing path generation (64 citations) solved one of the central geometric challenges in robotic surface finishing. Together, these studies established foundational computational frameworks for automatically generating robot control commands across geometrically complex workpieces. Beyond finishing processes, Asakawa extended his expertise into forging-type rapid prototyping and open CAM kernel development, reflecting a commitment to accessible, adaptable manufacturing technology. His work on error compensation using real-time shape measurement further demonstrates a sophisticated integration of sensing and control. With over 260 cumulative citations across a decade of focused research, Asakawa's contributions remain essential reading for engineers and researchers working at the intersection of robotic automation, CAD/CAM systems, and precision manufacturing.