Eigen - Re-orthogonalization of Rotation Matrix

Question

After multiplying a lot of rotation matrices, the end result might not be a valid rotation matrix any more, due to rounding issues (de-orthogonalized)

One way to re-

Answer 1

Singular Value Decomposition should be very robust. To quote from the reference:

Let M=UΣV be the singular value decomposition of M, then R=UV.

For your matrix, the singular-values in Σ should be very close to one. The matrix R is guaranteed to be orthogonal, which is the defining property of a rotation matrix. If there weren't any rounding errors in calculating your original rotation matrix, then R will be exactly the same as your M to within numerical precision.