I am using the package LazySets to compute the Minkowsky sum of two HPolyhedron and then extract the resulting constraints to feed them into my JuMP model.

For the 2D case, I can approximate the exact Polyhedron with overapproximate, like this:

```
n = 2
A = [Matrix{Float64}(I, n,n); -Matrix{Float64}(I, n,n)]
b = 0.1*ones(size(A,1))
hPoly = HPolyhedron(A, b)
minkowSum = hPoly ⊕ hPoly
overapproximate(minkowSum , 1e-3)
```

However, for higher dimensional Polyhedron (e.g. n=3) overapproximate throws an error. Is there a way to approximate the HPolyhedron resulting from the Minkowsky addition for n=3 with LazySets or Polyhedra?