Drift correction for industrial augemented reality applications
In a method for facilitating creation of a map of a real-world, process control environment, locations of a mobile device are tracked as a user moves through a mapped environment. A camera of the mobile device captures images of the mapped environment as the user moves through the mapped environment...
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Zusammenfassung: | In a method for facilitating creation of a map of a real-world, process control environment, locations of a mobile device are tracked as a user moves through a mapped environment. A camera of the mobile device captures images of the mapped environment as the user moves through the mapped environment, and the user indicates an intention to add a node to the map. One or more images of the captured images are provided to a machine learning (ML) model, and the ML model is trained to process images to recognize object types. The ML model may predict an object type corresponding to a specific object within a field of view of the camera. A display of the mobile device may then superimpose, on a real-world view presented to the user, an indication of the predicted object type to facilitate user designation of a descriptor for the new node. |
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