Samsung patents map compression for self-driving cars

1. A method comprising, by an electronic device: accessing sensor data captured by one or more mobile devices operating in a plurality of regions in an environment; generating, for each of the plurality regions, a plurality of graph embeddings associated with each of the mobile devices based on a compressed graph associated with each of the mobile devices constructed from the sensor data, wherein the compressed graph comprises a plurality of nodes and a plurality of compressed edges connecting the nodes across a plurality of layers; generating, for each of the plurality of regions based on the plurality of graph embeddings associated with each of the mobile devices, a refined graph associated with each of the mobile devices by reconfiguring one or more edges of the plurality of compressed edges across the plurality of layers in the compressed graph associated with each of the mobile devices; determining a token quantization to identify one or more of a plurality of text tokens of text information associated with each of the mobile devices to compress based on a fusion process of the plurality of text tokens and the plurality of graph embeddings associated with each of the mobile devices; identifying and removing non-prevalent edges from the plurality of compressed edges associated with each refined graph based on the identified text tokens to compress; generating a graph high-definition (HD) map associated with each of the mobile devices based on a fusion of the one or more refined graphs associated with the plurality of regions for each of the mobile devices; identifying, based on the graph HD map associated with each of the mobile devices, a plurality of prominent nodes and a plurality of prominent edges connecting the prominent nodes based on trace activations associated with the prominent edges; generating a compressed graph HD map for the environment based on the prominent nodes and prominent edges associated with the one or more mobile devices and environmental information associated with the environment; and using the compressed graph HD map to perform autonomous navigation and control.