Let $K \subseteq \mathbb{R}^n$ be a closed convex set containing the origin. Let $\Pi_K$ denote the Euclidean projection onto $K$.
I would like to show that for any fixed $x_0 \in K$, $$\sup_{x \in \mathbb{R}^n} \left|\|\Pi_K(x_0+x)-x_0\|^2 - \|\Pi_K(x)\|^2\right| < \infty, \tag{1}$$ or equivalently, $$\sup_{x \in \mathbb{R}^n} \left|\|\Pi_{K - \{x_0\}}(x)\|^2 - \|\Pi_K(x)\|^2\right| < \infty.$$
Note that $\|\Pi_K(x_0+x)-x_0\|^2$ can be rewritten as $\|\Pi_{K - \{x_0\}}(x)\|^2$ where $K-\{x_0\} := \{x-x_0 : x \in K\}$, so my question can be viewed as controlling the difference in the square lengths of the projections onto $K$ and a translated version $K-\{x_0\}$.
I do not know if this is true, but have not been able to either prove it or give a counterexample.
Note that this is a different statement than $$\sup_{x \in \mathbb{R}^n} \|\Pi_{K-\{x_0\}}(x) - \Pi_K(x)\|^2 < \infty.$$ I do not know if this implies or is implied by the previous claim. I also do not know if this is true or false.
They are related as follows: $$\|\Pi_{K - \{x_0\}}(x)\|^2 - \|\Pi_K(x)\|^2 = \|\Pi_{K-\{x_0\}}(x) - \Pi_K(x)\|^2 + 2\langle\Pi_{K-\{x_0\}}(x)-\Pi_K(x), \Pi_K(x)\rangle.$$
Any references/hints/suggestions are appreciated!
Update: although I am not able to parse HK Lee's justification, I believe his/her counterexample is correct. I have verified using a computer that $K=\{(x,y) : y \ge x^2\}$ and $x_0 = (0,1)$ does not satisfy (1) above because the expression tends to $\infty$ for $x=(n,n)$ as $n \to \infty$. (But showing this analytically is messy since one needs to solve a cubic.)
My hunch is that the increasing change in curvature is the culprit in the above counterexample, and I conjecture that (1) does hold if $K$ is a polyhedron (finitely many linear constraints). But maybe that is a question for another time.