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Instead of perturbing each pixel in the input image at random, we can choose to dither by a predetermined amount depending on the pixel’s position in the image. This can be achieved using a threshold map; a small, fixed-size matrix where each entry tells us the amount by which to perturb the input value , producing the dithered value . This matrix is tiled across the input image and sampled for every pixel during the dithering process.  The following describes a dithering function for a 4×4 matrix given the pixel raster coordinates :

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Many premium robot vacuums also use intel from past cleaning sessions to create AI-driven cleaning plans for a more efficient clean in specific rooms going forward. If one area of the home is consistently dirtier than the others (like in the kitchen or near the front door), AI modes like Roborock SmartPlan, Narwal Freo, and Dreame CleanGenius will remember that for next time.

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