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About

Takehisa Yairi is a versatile robotics and artificial intelligence researcher whose work spans aerial robotics, mobile robot mapping, human-robot interaction, and AI-based systems health management. His most influential contribution is a comprehensive 2017 survey on aerial robotics and UAV developments, which has garnered 68 citations and stands as a key reference for researchers entering the field. Yairi has made significant strides in mobile robot autonomy, developing innovative localization-free mapping frameworks using dimensionality reduction techniques and covisibility-based map learning methods that enable robots to construct environmental representations without precise self-localization. His work extends into space robotics, where he explored skill acquisition learning for precise autonomous assembly tasks. Yairi has also contributed meaningfully to human-robot interaction, investigating how social factors like noise and appearance influence the design of aerial robots, and advancing facial expression recognition for natural human-computer interaction. More recently, his research has addressed the robustness of AI-driven prognostics and systems health management, reflecting a growing focus on dependable AI. With over 170 cumulative citations across diverse domains, Yairi represents a broad and impactful voice in intelligent robotics research.