Ukyo Katsura

Papers

Total Citations

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About

Ukyo Katsura is a robotics researcher whose work centers on spatial perception and change detection for autonomous systems. His primary contributions lie in developing fast, reliable methods for robots to identify differences in their environment over time—a critical capability for applications like search and rescue, security, and surveillance. Katsura’s most influential work, "Spatial change detection using voxel classification by normal distributions transform" (2019, 11 citations), introduces a technique that allows mobile robots equipped with RGB-D or stereo cameras to quickly detect spatial changes by classifying 3D voxels using the normal distributions transform. This approach enables robots to efficiently compare real-time sensor data against a pre-existing high-precision 3D map, significantly improving the speed and accuracy of change detection. His earlier foundational paper on the same topic (2019, 4 citations) laid the groundwork for this innovation. Though his citation counts are modest, Katsura’s work addresses a practical bottleneck in field robotics—how to make spatial change detection computationally feasible for real-time operation. His research is particularly valuable for autonomous systems that must navigate dynamic, unstructured environments, offering a pathway toward more responsive and situationally aware robots.