METHOD FOR SEMANTIC LOCALIZATION OF AN UNMANNED AERIAL VEHICLE A computer-implemented method comprises receiving an image captured by a camera on an unmanned aerial vehicle (UAV). The image depicts an environment below the UAV. A feature mask associated with the image is generated via a machine learning model that is trained to identify and semantically label pixels representing the environment depicted in the image. One or more reference tiles associated with the environment are retrieved. The reference tiles are associated with particular geographic locations and specify semantically labeled pixels representing the geographic locations. The semantically labeled pixels of the feature mask are correlated with the semantically labeled pixels of at least one of the one or more reference tiles to determine the geographic location of the UAV in the environment. K.UAV IS TRAVELLING GNSS BASED YES 515 51 r o, PREDICT LOCATION DETERMINE LOCATION BASED ON IMAGE BASED ON GNSS CAPTURE SIGNALS PREDICTED NO 525 YS 530 , DETERMINE LOCATION PERFORM CONTIGENCY BASED ON PREDICTED OPERATIONS
Method for semantic localization of an unmanned aerial vehicle
2023-10-19
Patent
Electronic Resource
English
Method for Semantic Localization of an Unmanned Aerial Vehicle
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