Ryosuke Kataoka

Papers

Total Citations

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About

Ryosuke Kataoka is a robotics researcher specializing in simultaneous localization and mapping (SLAM), with a particular focus on enhancing LiDAR-based navigation in challenging environments. His key research areas include scan-matching algorithms, sensor fusion, and global registration techniques for autonomous systems. Kataoka’s major contribution lies in developing novel methods that leverage not only geometric point cloud data but also LiDAR intensity and near-infrared information to improve localization accuracy. His 2021 paper on "ICP-based SLAM Using LiDAR Intensity and Near-infrared Data" (10 citations) demonstrates how incorporating radiometric data can overcome the limitations of shape-based scan-matching in feature-sparse environments. He further advanced this work by addressing the critical problem of initial alignment in SLAM, showing that global registration using LiDAR intensity and water puddle measurements can significantly boost performance (2 citations). While his citation counts reflect the early stage of his career, Kataoka’s innovative approach to multi-modal sensor integration represents a promising direction for robust autonomous navigation in real-world conditions, particularly in environments where traditional methods struggle with insufficient geometric features.