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I'm grateful for the Raycasting example file demonstrating how to 'stick' objects onto other objects. However its limitation becomes apparent when one object is larger than the frequency perturbations of the underlying object (see attached image). Ideally one would sample at a higher rate to gather multiple point data (in this case Normals) and filter (average, for example) to better represent the interface between the surfaces.
Getting closest points seems better suited to Getting neighboring points in that there is control of search radius, which can be adjusted to best represent the surface perturbation frequency. I've included an image of an ICETree, which is the most basic approach - but despite its simplicity is not at all straightforward to recreate in Canvas. I have looked through the docs and it is not obvious or intuitive how to manipulate arrays on a per-point basis.
Beside a demonstration of an equivalent Canvas solution it would be great if there were also an explanation of the Canvas approach - why it is handled in the way that it is.
And my apologies if this has been addressed elsewhere - I will continue to hunt among the forum & tutorials while awaiting a reply.
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