jats:pIf an initial frame of vectors is related to a final frame of vectors by, in geometric algebra (GA) terms, a jats:italicrotor</jats:italic>, or in linear algebra terms, an jats:italicorthogonal transformation</jats:italic>, we often want to find this rotor given the initial and final sets of vectors. One very common example is finding a rotor or orthogonal matrix representing rotation, given knowledge of initial and transformed points.</jats:p>jats:pIn this paper, we discuss methods in the literature for recovering such rotors and then outline a GA method, which generalises to cases of any signature and any dimension, and which is not restricted to orthonormal sets of vectors. The proof of this technique is both concise and elegant and uses the concept of jats:italiccharacteristic multivectors</jats:italic> as discussed in the book by Hestenes and Sobczyk, which contains a treatment of linear algebra using geometric algebra. Expressing orthogonal transformations as rotors, enables us to create jats:italicfractional transformations</jats:italic> and we discuss this for some classic transforms. In real applications, our initial and/or final sets of vectors will be noisy. We show how to use the characteristic multivector method to find a ‘best fit’ rotor between these sets and compare our results with other methods.</jats:p>