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About

Akinobu Sasamura is a robotics researcher specializing in autonomous inspection systems for industrial plants, with a focus on visual and acoustic monitoring. His work centers on developing methods for mobile robots to detect anomalies and changes in complex environments, enhancing safety and operational efficiency in facilities like refineries. Sasamura’s major contributions include a system for change detection in 3D space using image pairs from mobile robot patrols, enabling autonomous plant visual inspection by comparing past and current video footage with pose information. He also pioneered acoustic monitoring with autoencoders, allowing robots to identify abnormal sounds during patrols, and proposed a sequential filtering technique for detecting surface changes on pipes from inspection videos. His most-cited paper, “Change Detection in Image Pairs for Plant Inspection Using Mobile Robot” (2025), has garnered 5 citations, reflecting its relevance in industrial robotics. With additional works on pipe inspection and acoustic anomaly detection, Sasamura’s research advances the automation of routine inspections, reducing human risk and improving reliability. His innovative approaches to integrating computer vision and machine learning for real-world industrial applications mark him as a key contributor to the field of autonomous robotics.