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About

Yasuyoshi Kaneko is a robotics and automation researcher whose work spans intelligent welding systems, whole-body force sensation, and rehabilitation robotics. His most influential contributions lie in advancing robotic welding technology, where he pioneered neural network and fuzzy logic approaches to estimate and control weld pool penetration depth in real time — a notoriously difficult sensing challenge. His series of welding-focused publications from the mid-1990s through the mid-2000s, including work on pulsed MIG welding, switch-back welding, and adaptive image-processing control, collectively demonstrate a sustained effort to bring intelligent automation to high-precision manufacturing environments. Kaneko's most-cited work (64 citations) introduced a shell-shaped end-effector enabling whole-body force sensation in robots — a meaningful step toward safer human-robot interaction by allowing force detection across an entire robotic surface rather than at isolated points. More recently, his research has expanded into rehabilitation robotics, proposing automated systems for quantitatively measuring upper-limb range of motion, and into teleoperation using hybrid electric-hydraulic actuators for hazardous environments. Across these diverse domains, Kaneko's career reflects a consistent focus on making robots more perceptive, adaptive, and practically useful in both industrial and human-centered applications.