It isn't immediately clear what the question intends by the term "rotor" ---
https://en.wikipedia.org/wiki/Rotor_(mathematics) lists three overlapping definitions. Reading between the lines, it seems that
the target universe comprises proper (continuous rigid) transformations fixing
the origin in Euclidean space with n dimensions. But bearing in mind that
similar elementary practical algorithms remain currently (as far as I know)
almost entirely absent from published sources, it might be worthwhile to float
a more general discussion here.
So let me assume initially that "rotor" means the same as "even versor",
ie. product of an even number of vectors in some given complex Cifford algebra;
and (initially at any rate) exclude parabolic, isoclinic, or half-turn factors,
along with any other nasties that I may have overlooked ...
Example: quaternions in 3-space. Clifford signature equals (+1,+1,+1) ,
or (-1,-1,-1) if you insist (sigh!); quaternion axes i, j, k map to
g f, e g, f e in terms of Clifford generators e, f, g .
Remark: it is advisable to abandon the almost universal convention mapping
vectors to points, which though sustainable in 3-space (at the cost of some
confusion), causes increasing inconvenience elsewhere. Here instead generators
u, v, w, ... represent coordinate hyperplanes, and the product of orthogonal
blades represents subspace intersection.
In n-space an elementary rotation X , through angle s , fixing axial coline
represented by normalised bivector L , is represented by
X = cos(s/2) + sin(s/2) L ;
and analogous representations apply to translation and boost.
[ If the sign of L is ambiguous, it is always possible instead to select
s = min(s, Pi-s) . However, beware that in dimension n > 3 it is in general
impossible to transform some coline through the origin into another via a single
elementary rotation! ]
Interpolation by versors between rotors X, Y is in principle achievable
via product
Z(t) = X^(1-t) Y^t in range 0 <= t <= 1 ;
where ^ denotes multivector exponentiation, implemented via exponential &