KR KR20250061796A
The present invention relates to a q-block-based parallel spatiotemporal operation system, which arranges an operation flow based on an anchor cube, calculates an importance score based on metadata of each unit cube to allocate the importance score to a parallel operation queue, and automatically optimizes the operation flow, path search, and operation priority through ai-based reinforcement learning. It can be applied to forming spatiotemporal graphs through anchor-to-anchor connections between multiple q-blocks, a* algorithm-based path search and real-time simulation, autonomous navigation, and spatiotemporal prediction.
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