Relative-pose-orthant clustering (control-oriented Neural Collapse)

Extends Neural Collapse-style within-class variance collapse to visual-control regression pipelines with no explicit label set, by defining implicit classes from the sign pattern (orthant) of a relative pose vector — e.g. object-to-target displacement — and measuring whether visual representations cluster by that orthant just as classifier representations cluster by label.