When a robot impacts its environment, it undergoes a large and rapid (though not quite instantaneous) change in velocity. Mode detection and state estimation in these brief periods are incredibly difficult, so it makes very little sense to apply feedback on these varying and imprecise velocity estimates. However, this uncertainty only applies to a subspace of velocities. In a new preprint, we project velocities onto an impact invariant subspace, preserving control authority in this subspace without spuriously reacting to impact-driven uncertainty.