Methods and systems for using trained generative adversarial networks to impute 3d data for facilities management and operations

A computing system for using a trained generative adversarial network to improve vehicle orientation and navigation, comprising:

• one or more processors, and
• one or more memories having stored thereon computer-executable instructions that, when executed, cause the computing system to:
• load a semantically-segmented 3D point cloud into a virtual reality simulation environment;
• process the 3D point cloud to identify at least one agricultural area;
• and
• display an output based on the processing of the 3D point cloud in the virtual reality simulation environment, wherein the output includes at least one attribute corresponding to the agricultural area.

A non-transitory computer-readable medium having stored thereon computer-executable instructions that, when executed, cause a computer to:

• load a semantically-segmented 3D point cloud into a virtual reality simulation environment;
• process the 3D point cloud to identify at least one agricultural area;
• and
• display an output based on the processing of the 3D point cloud in the virtual reality simulation environment, wherein the output includes at least one attribute corresponding to the agricultural area.