Transformation matrix
The transformation matrix is a much wider concept but for purpose of orientation in 3D space, we will restrict it into a rotation matrix. So transformation matrix transform (wow) any vector from one reference frame in the other:
Rotation matrix rotate any vector about a specific axis and about a set angle (in this example rotation of vector
It is important to see the difference between the transformation of a vector between references frames and the rotation of a vector. These two are related to each other but not the same.
Assuming that a certain reference system (
Due to the orthogonality of this matrix, its inverse is equal to its transposition:
The transformation matrix defines explicitly the orientation and in a very simple way allows to perform the transformation of vectors from one system to another. It is also quite intuitive. Unfortunately, due to numerical inaccuracies, it quickly happens that the matrix is not normalized (loses orthonormality) and it is necessary to normalize it, which is a rather computationally expensive process.
Euler angles can be easily extracted from the transformation matrix. This can be seen very well when one writes the transformation matrix in 3D space as a complex of 3 basic rotations (rotations about 3 principal axes of the global system). For the rotation scheme
From matrix (
You can see here exactly the problem of determining the Euler angles in the surrounding of the singular point (
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