Systems and methods for providing vehicle cognition through localization and semantic mapping are provided. Localization may involve in vehicle calculation of voxel signatures, such as by hashing weighted voxel data (S900, S910) obtained from a machine vision system (110), and comparison of calculated signatures to cached data within a signature localization table (630) containing previously known voxel signatures and associated geospatial positions. Signature localization tables (630) may be developed by swarms of agents (1000) calculating signatures while traversing an environment and reporting calculated signatures and associated geospatial positions to a central server (1240). Once vehicles are localized, they may engage in semantic mapping. A swarm of vehicles (1400, 1402) may characterize assets encountered while traversing a local environment. Asset characterizations may be compared to known assets within the locally cached semantic map. Differences of omission and commission between observed assets and asset characterizations with the local map cache (1860) may be reported to a central server (1800). Updates to the local signature cache (1852) and/or local map cache (1862) may be transmitted from the central server (1800) back down to vehicles within the swarm (1840).
Systems and methods for providing vehicle cognition