Space Filling Curve

Space-filling curves are continuous paths that traverse every point in a multi-dimensional space, offering efficient ways to organize and access data. Current research focuses on improving their application in diverse fields, including optimizing search algorithms (using Hilbert curves for efficient sampling), designing modular robots (exploring non-cubic geometries), and enabling robotic exploration with online obstacle avoidance. These advancements demonstrate the practical utility of space-filling curves in areas like data analysis, robotics, and knowledge graph construction, highlighting their potential to solve complex problems across various scientific disciplines.