**Rotations, Quaternions, and
Direction Cosines**

Quaternions have bothered me for a long time. A colleague of mine once handed me copies of some pages from books that talked about “quaternions,” also called “spinors,” “spin matrices,” and a host of other names. What bothered me was that I was already familiar with Eulerian rotations, and I wondered what quaternions did differently that made them useful.

Here is my best answer to date. This paper answers several particular questions about using quaternions and direction cosines for performing rotations. It also relates quaternions to Eulerian rotations. The questions include the following.

1. I want to rotate a vector by a specified angle about an arbitrary axis of rotation. Where does the vector end up? Answer: Use quaternions.

2. I want to rotate a vector from Point 0 to Point 1 (these points are assumed to be a unit distance from the origin). What is the shortest path of rotation? What is the axis of rotation? What is the angle of rotation? Answer: Use quaternions.

3. To find an angle bisector between two vectors, A and B, I want to find the axis of rotation such that a 180 degree rotation of A maps it to B. How do I do this? Answer: Use quaternions.

4. How do I rotate from one reference frame to another? Answer: Use direction cosines.

5. When rotating between one frame and another using direction cosines, where is the axis of rotation, and what is the angle of rotation?

6. What is the direction and length of the differential tangential element described by a differential rotation about an arbitrary axis?

To begin, we first must learn a bit about quaternions. These mathematics were apparently developed by Gauss (but never published by him) and separately by William Hamilton. One text of mine says that

On the evening of October 16, 1843, William Rowan Hamilton was walking with his wife along the Royal Canal in Dublin when the answer leapt to his mind, the fruit of years of reflection [a pun?]. With his knife he then and there carved on a stone on Brougham Bridge the formulas

_{}

which in today’s notation,

_{} _{} _{}

take the form

_{}

_{} (and cyclic
permutations)

(I have changed the notation slightly to conform with my own standards.) The author has a footnote that reads

In the same city on June 21, 1972
President Eamon de Valera told one of the authors that, while in jail one evening
in 1916, scheduled to be shot the next morning, he wrote down the formula of
which he was so fond, _{}.

Unfortunately I do not have the complete reference, and I know only that it is in Chapter 41, entitled “Spinors,” of some book.

Piecing together bits and pieces from several such references, none complete, some with sloppy notation, I managed to compile the following practical guide. First, one can discuss a sequence of rotations of the coordinate system about specified axes. Second, one can pick an arbitrary axis (by means of its direction cosines) and rotate a point about it.

Let us
consider the following sequence of rotations of a coordinate system. The point, (x,y,z) remains fixed, and we
want to know the location of the point in the new coordinate system after the
sequence of rotations is complete.
First, we place the point coordinates in a complex matrix, _{}.

_{}

Next, we
define a matrix, _{}, that contains the rotations

_{}

The angles and their associated axes of rotations are as follows. The order of rotation is important.

1. f: Rotation about the z axis, the x axis moves toward the positive y axis.

2. q: Rotation about the new x axis, the y axis moves toward the positive z axis.

3. y: Rotation about the new z axis, the x axis moves toward the positive y axis.

Alternatively, one could consider the coordinate system fixed, and the point being rotated. In this case, the angles and their associated axes of rotations are as follows.

1. f: Rotation about the z axis, f is measured from the x axis toward the negative y axis.

2. q: Rotation about the x axis, q is measured from the y axis toward the negative z axis.

3. y: Rotation about the z axis, y is measured from the x axis toward the negative y axis.

To obtain the new coordinates described by the _{} matrix, one applies
the formula

_{}

(Actually, the last term should be the conjugate transpose
of _{}, but since _{} is self-adjoint, the
conjugate transpose is the inverse.)
The _{} matrix is given by

_{}

We note
that _{} can be decomposed and
written in terms of the Pauli spin matrices _{} given above.

_{}

_{}

where we also have used the unit matrix, _{}.

Now we turn
to rotating a point by an angle, _{}, about an arbitrary axis in space. The axis can be described in terms of the angles it makes with
the coordinate axes:

a Angle with the x axis

b Angle with the y axis

g Angle with the z axis

The cosines of these angles are the direction cosines:

_{}

_{}

_{}

The rotation occurs in the clockwise direction from the
perspective of a person situated at the origin and looking along the positive
rotational axis. To perform the
rotation, one uses the _{} matrix described
above and then forms the _{} matrix as follows.

_{}

The new coordinates, described by the _{} matrix, are obtained
through

_{}

We note
that the computation of _{} is easy and is given
by

_{}

If one prefers, the total transformation can be described by

_{}

This equation is very easy to compute. _{} can generally be
computed as the dot product of two unit vectors, _{} as the norm of the
cross product, and _{}. Thus, the above
equation reduces to the following.

_{}

I want to rotate a vector by a specified angle about an arbitrary axis of rotation. Where does the vector end up?

Begin by
defining the axis by its direction cosines _{}, the angle of rotation by _{} (measured
clockwise as viewed from the origin looking in the direction of the positive
axis of rotation), and the original vector location by the unprimed coordinates
_{}; then the rotation carries the vector to the primed
coordinates (in the same reference frame) given by

_{}

I want to rotate a vector from Point 0 to Point 1 (these points are assumed to be a unit distance from the origin). What is the shortest path of rotation? What is the axis of rotation? What is the angle of rotation?

We begin
with the normalized coordinates describing the two directions: _{} and _{}. We know that the
shortest arc between these two directions will lie in the plane of these two
points and the origin. The equation of
the plane is

_{}

where

_{}

_{}

_{}

When these parameters are normalized, they become the direction cosines of the normal vector to the plane. This normal vector is also the desired axis of rotation:

_{}

_{}

_{}

Finally, we know that the angle of rotation will be equivalent to the angle included by Point 0, the origin, and Point 1. This angle can be calculated by

_{}

To find an angle bisector between two vectors, A and B, I want to find the axis of rotation such that a 180 degree rotation of A maps it to B. How do I do this?

We begin by
assuming that we have two unit vectors _{} and _{}. Applying the
rotation formula,

_{}

we reduce it with the knowledge that _{}.

_{}

Now, we
need to solve for the direction cosines of the rotation axis, _{}. Multiplying each
side of the equation by _{} and equating terms on
an element-by-element basis, one quickly arrives at the three equations (each
repeated three times),

_{} _{} _{}

Recognizing that

_{}

one has that

_{} _{} _{}

_{} is easy to obtain
because it is half of the angle included by the two vectors. That is,

_{}

_{}

Note that _{} is always positive
since the included angle must be less than 90°. If the two vectors are diametrically opposed, then the answer is
non-unique, and the procedure fails.
For nearly opposed vectors, severe cancellation _{} in the numerator
could affect the numerical accuracy of the result. If severe cancellation in one direction cosine is detected, it is
best to discard the result, compute the other direction cosines, and apply the
constraint _{}. Severe cancellation
can also affect two or all three direction cosines. Perhaps double precision is the best defense here.

As an alternative formulation of the angle bisector problem, one could consider a rotation about an axis perpendicular to the plane of the two vectors by an amount equal to half of the included angle. The resulting vector will be the angle bisector of the two original vectors. In this case, severe cancellation can occur in the computation of the perpendicular to the two original vectors.

How do I rotate from one reference frame to another?

When
rotating from one reference frame to another, we define one coordinate system
(the unprimed coordinates) with respect to the other (primed) coordinate
system. We do this by finding the
direction cosines of each axis of the unprimed coordinate system in terms of
the primed system. For instance, the
direction cosines of the x axis are given by _{}. Placing all of
these direction cosines in a matrix gives us the rotation that we desire:

_{}

As an example, we consider the unprimed system situated so that its z axis coincides with the z prime axis, but the frame is rotated so that the x axis coincides with the y prime axis. The direction cosines are found by

_{} _{} _{}

_{} _{} _{}

_{} _{} _{}

or

_{}

Thus, the point (1,0,0) in the unprimed system maps to (0,1,0) in the primed system.

One further note is that the inverse of the matrix given above is merely the transpose of the matrix (that is, the matrix is self adjoint). Hence,

_{}

When rotating between one frame and another using direction cosines, where is the axis of rotation, and what is the angle of rotation?

If one completes a rotation as described in Question 5, it is natural to ask if one can determine the angular extent of the rotation and the axis of rotation. To answer these questions, we compare the quaternion relationship

_{}

to the direction cosine relationship

_{}

on an element-by-element basis. Comparison of the diagonal elements yields that

_{} _{} _{}

By adding corresponding elements on opposite sides of the
diagonal _{}, and substituting the above expressions, one easily obtains
that

_{}

_{}

_{}

For our purposes, any of these equations will do. The sign is chosen so that the cosine calculation and the following direction cosine calculations lie between –1 and 1 (the previous direction cosine calculations must remain real). By subtracting corresponding elements, one obtains

_{} _{} _{}

These formula for the direction cosines are superior to the previous ones because sign information is retained. The previous set of direction cosine equations was derived only to facilitate the derivation of the formulas for the cosine of the angle of rotation.

What is the direction and length of the differential tangential element described by a differential rotation about an arbitrary axis?

_{}

or

_{}

If _{} be vanishingly small,
then we obtain

_{}

or

_{}

where

_{}

Thus,

_{}

describes the tangent to the great circle. The square of the length of a differential tangential element is

_{}

For
example, consider a rotation about the z axis so that _{} and _{}. The direction of
the tangent vector is

_{}

or _{} and _{}. The length of the
differential tangent element is

_{}

or _{}. (Note that this is _{} if the coordinates
are converted to cylindrical coordinates.)