# Rotations, Orientation and Quaternions

This example reviews concepts in three-dimensional rotations and how quaternions are used to describe orientation and rotations. Quaternions are a skew field of hypercomplex numbers. They have found applications in aerospace, computer graphics and virtual reality. In MATLAB®, quaternion mathematics can be represented by manipulating the `quaternion` class.

## Contents

The `fusiondemo.drawRotation` class is used to illustrate several portions of this example.

dr = fusiondemo.drawRotation;

## Rotations in Three Dimensions

All rotations in 3D can be defined by an axis of rotation and an angle of rotation about that axis. Consider the 3D image of a teapot in the leftmost plot. The teapot rotated by 45 degrees around the Z-axis is in the second plot. A more complex rotation of 15 degrees around the axis [1 0 1] is shown in the third plot. Quaternions encapsulate the axis and angle of rotation, and have an algebra for manipulating these rotations. The `quaternion` class, and this example, use the "right-hand rule" convention to define rotations. That is, positive rotations are clockwise around the axis of rotation when viewed from the origin.

dr.drawTeapotRotations;

## Point Rotation

The vertices of the teapot were rotated about the axis of rotation in the reference frame. Consider a point (0.7, 0.5) rotated 30 degrees about the Z-axis.

figure; dr.draw2DPointRotation(gca);

## Frame Rotation

Frame rotation is, in some sense, the opposite of point rotation. In frame rotation, the points of the object stay fixed, but the frame of reference is rotated. Again, consider the point (0.7, 0.5). Now the reference frame is rotated by 30 degrees around the Z-axis. Note that while the point (0.7, 0.5) stays fixed, it has different coordinates in the new, rotated frame of reference.

figure; dr.draw2DFrameRotation(gca);

## Orientation

Orientation refers to the angular displacement of an object relative to a frame of reference. Typically, orientation is described by the rotation that causes this angular displacement from a starting orientation. In the Sensor Fusion and Tracking Toolbox™, orientation is defined as the rotation that takes a quantity in a parent reference frame to a child reference frame. Orientation is usually given as a quaternion, rotation matrix, set of Euler angles, or a rotation vector. It is useful to think about orientation as a frame rotation - the child reference frame is rotated relative to the parent frame.

Consider an example where the child reference frame is rotated 30 degrees around the vector [1/3 2/3 2/3].

figure; dr.draw3DOrientation(gca, [1/3 2/3 2/3], 30);

## Quaternions

Quaternions are numbers of the form

where

and and are real numbers. In the rest of this example, the four numbers and are referred to as the *parts* of the quaternion.

## Quaternions for Rotations and Orientation

The axis and the angle of rotation are encapsulated in the quaternion parts. For a unit vector axis of rotation [x,y,z], and rotation angle , the quaternion describing this rotation is

Notable here is that to describe a rotation using a quaternion, the quaternion must be a *unit quaternion*. A unit quaternion has a norm of 1, where the norm is defined as

There are a variety of ways to construct a quaternion number in MATLAB, for example

q1 = quaternion(1,2,3,4)

q1 = quaternion 1 + 2i + 3j + 4k

Arrays of quaternions can be made in the same way:

quaternion([1 10; -1 1], [2 20; -2 2], [3 30; -3 3], [4 40; -4 4])

ans = 2x2 quaternion array 1 + 2i + 3j + 4k 10 + 20i + 30j + 40k -1 - 2i - 3j - 4k 1 + 2i + 3j + 4k

Arrays with four columns can also be used to construct quaternions with each column representing a quaternion part

qmgk = quaternion(magic(4))

qmgk = 4x1 quaternion array 16 + 2i + 3j + 13k 5 + 11i + 10j + 8k 9 + 7i + 6j + 12k 4 + 14i + 15j + 1k

Quaternions can be indexed and manipulated just like any other array:

qmgk(3)

ans = quaternion 9 + 7i + 6j + 12k

reshape(qmgk,2,2)

ans = 2x2 quaternion array 16 + 2i + 3j + 13k 9 + 7i + 6j + 12k 5 + 11i + 10j + 8k 4 + 14i + 15j + 1k

[q1; q1]

ans = 2x1 quaternion array 1 + 2i + 3j + 4k 1 + 2i + 3j + 4k

## Quaternion Math

Quaternions have well-defined arithmetic operations. Addition and subtraction are similar to complex numbers: parts are added/subtracted independently. Multiplication is more complicated because of the earlier equation

This means that multiplication of quaternions is not commutative. That is, for quaternions and . However, every quaternion has a multiplicative inverse, so quaternions can be divided. Arrays of the `quaternion` class can be added, subtracted, multiplied and divided in MATLAB.

q = quaternion(1,2,3,4); p = quaternion(-5,6,-7,8);

Addition

p + q

ans = quaternion -4 + 8i - 4j + 12k

Subtraction

p - q

ans = quaternion -6 + 4i - 10j + 4k

Multiplication

p*q

ans = quaternion -28 - 56i - 30j + 20k

Multiplication in the reverse order (note the different result)

q*p

ans = quaternion -28 + 48i - 14j - 44k

Right division of `p` by `q` is equivalent to

p./q

ans = quaternion 0.6 + 2.2667i + 0.53333j - 0.13333k

Left division of `q` by `p` is equivalent to

p.\q

ans = quaternion 0.10345 + 0.2069i + 0j - 0.34483k

The conjugate of a quaternion is formed by negating each of the non-real parts, similar to conjugation for a complex number:

conj(p)

ans = quaternion -5 - 6i + 7j - 8k

Quaternions can be normalized in MATLAB

pnormed = normalize(p)

pnormed = quaternion -0.37905 + 0.45486i - 0.53067j + 0.60648k

norm(pnormed)

ans = 1

## Point and Frame Rotations with Quaternions

Quaternions can be used to rotate points in a static frame of reference, or to rotate the frame of reference itself. The `rotatepoint` function rotates a point using a quaternion q through the following equation:

where is a quaternion formed as

and indicates quaternion conjugation. Note the above quaternion multiplication results in a quaternion with the real part, a, equal to 0. The b,c, and d parts of the result form the rotated point (b,c,d).

Consider the example of point rotation from above. The point (0.7, 0.5) was rotated 30 degrees around the Z-axis. In 3-dimensions this point has a 0 Z-coordinate. Using the axis-angle formulation, a quaternion can be constructed using [0 0 1] as the axis of rotation.

```
ang = deg2rad(30);
q = quaternion(cos(ang/2), 0, 0, sin(ang/2));
pt = [0.7, 0.5, 0]; % Z-coordinate is 0 in the X-Y plane
ptrot = rotatepoint(q, pt)
```

ptrot = 0.3562 0.7830 0

Similarly, the `rotateframe` function takes a quaternion q and point v to compute

Again the above quaternion multiplication results in a quaternion with 0 real part. The (b,c,d) parts of the result form the coordinate of the point v in the new, rotated reference frame. Using the `quaternion` class

ptframerot = rotateframe(q, pt)

ptframerot = 0.8562 0.0830 0

It should be clear that a quaternion and its conjugate have opposite effects because of the symmetry in the point and frame rotation equations. Rotating by the conjugate "undoes" the rotation.

rotateframe(conj(q), ptframerot)

ans = 0.7000 0.5000 0

or equivalently, because of the symmetry of the equations

rotatepoint(q, ptframerot)

ans = 0.7000 0.5000 0

## Other Rotation Representations

Often rotations and orientations are described using alternate means: Euler angles, rotation matrices, and/or rotation vectors. All of these interoperate with quaternions in MATLAB.

Euler angles are frequently used because they are easy to interpret. Consider a frame of reference rotated by 30 degrees around the Z-axis, then 20 degrees around the Y-axis, then -50 degrees around the X-axis. Note here, and throughout, the rotations around each axis are *intrinsic* - each subsequent rotation is around the newly created set of axes. i.e. the second rotation is around the "new" Y-axis created by the first rotation, not around the original Y-axis.

figure; euld = [30 20 -50]; dr.drawEulerRotation(gca, euld);

To build a quaternion from these Euler angles for the purpose of frame rotation, use the `quaternion` constructor. Since the order of rotations is around the Z-axis first, then around the new Y-axis, and finally around the new X-axis, the `'ZYX'` flag is used.

qeul = quaternion(deg2rad(euld), 'euler', 'ZYX', 'frame')

qeul = quaternion 0.84313 - 0.44275i + 0.044296j + 0.30189k

The `'euler'` flag indicates that the first argument is in radians. If the argument is in degrees, use the `'eulerd'` flag.

qeuld = quaternion(euld, 'eulerd', 'ZYX', 'frame')

qeuld = quaternion 0.84313 - 0.44275i + 0.044296j + 0.30189k

To convert back to Euler angles

rad2deg(euler(qeul, 'ZYX', 'frame'))

ans = 30.0000 20.0000 -50.0000

Equivalently, the `eulerd` method can be used.

eulerd(qeul, 'ZYX', 'frame')

ans = 30.0000 20.0000 -50.0000

Alternatively, this same rotation can be represented as a rotation matrix:

```
rmat = rotmat(qeul, 'frame')
```

rmat = 0.8138 0.4698 -0.3420 -0.5483 0.4257 -0.7198 -0.1926 0.7733 0.6040

The conversion back to quaternions is similar

quaternion(rmat, 'rotmat', 'frame')

ans = quaternion 0.84313 - 0.44275i + 0.044296j + 0.30189k

Just as a quaternion can be used for either point or frame rotation, it can be converted to a rotation matrix (or set of Euler angles) specifically for point or frame rotation. The rotation matrix for point rotation is the transpose of the one for frame rotation. To convert between rotation representations, it is necessary to specify `'point'` or `'frame'`.

The rotation matrix for the Point Rotation section of this example is

```
rotmatPoint = rotmat(q, 'point')
```

rotmatPoint = 0.8660 -0.5000 0 0.5000 0.8660 0 0 0 1.0000

To find the location of the rotated point, right-multiply `rotmatPoint` by the transposed array `pt`.

rotmatPoint * (pt')

ans = 0.3562 0.7830 0

The rotation matrix for the Frame Rotation section of this example is

```
rotmatFrame = rotmat(q, 'frame')
```

rotmatFrame = 0.8660 0.5000 0 -0.5000 0.8660 0 0 0 1.0000

To find the location of the point in the rotated reference frame, right-multiply `rotmatFrame` by the transposed array `pt`.

rotmatFrame * (pt')

ans = 0.8562 0.0830 0

A rotation vector is an alternate, compact rotation encapsulation. A rotation vector is simply a three element vector which represents the unit length axis of rotation scaled-up by the angle of rotation in radians. There is no frame-ness or point-ness associated with a rotation vector. To convert to a rotation vector:

rv = rotvec(qeul)

rv = -0.9349 0.0935 0.6375

To convert to a quaternion

```
quaternion(rv, 'rotvec')
```

ans = quaternion 0.84313 - 0.44275i + 0.044296j + 0.30189k

## Distance

One advantage of quaternions over Euler angles is the lack of discontinuities. Euler angles have discontinuities that vary depending on the convention being used. The `dist` function compares the effect of rotation by two different quaternions. The result is a number in the range of 0 to `pi`. Consider two quaternions constructed from Euler angles:

eul1 = [0, 10, 0]; eul2 = [0, 15, 0]; qdist1 = quaternion(deg2rad(eul1), 'euler', 'ZYX', 'frame'); qdist2 = quaternion(deg2rad(eul2), 'euler', 'ZYX', 'frame');

Subtracting the Euler angles, you can see there is no rotation around the Z-axis or X-axis.

eul2 - eul1

ans = 0 5 0

The difference between these two rotations is five degrees around the Y-axis. The `dist` shows the difference as well.

rad2deg(dist(qdist1, qdist2))

ans = 5.0000

For Euler angles such as `eul1` and `eul2`, computing angular distance is trivial. A more complex example, which spans an Euler angle discontinuity, is:

eul3 = [0, 89, 0]; eul4 = [180, 89, 180]; qdist3 = quaternion(deg2rad(eul3), 'euler', 'ZYX', 'frame'); qdist4 = quaternion(deg2rad(eul4), 'euler', 'ZYX', 'frame');

Though `eul3` and `eul4` represent nearly the same orientation, simple Euler angle subtraction gives the impression that these two orientations are very far apart.

euldiff = eul4 - eul3

euldiff = 180 0 180

Using the `dist` function on the quaternions shows that there is only a two-degree difference in these rotations

euldist = rad2deg(dist(qdist3, qdist4))

euldist = 2.0000

A quaternion and its negative represent the same rotation. This is not obvious from subtracting quaternions but the `dist` function makes it clear.

qpos = quaternion(-cos(pi/4), 0 ,0, sin(pi/4))

qpos = quaternion -0.70711 + 0i + 0j + 0.70711k

qneg = -qpos

qneg = quaternion 0.70711 + 0i + 0j - 0.70711k

qdiff = qpos - qneg

qdiff = quaternion -1.4142 + 0i + 0j + 1.4142k

dist(qpos, qneg)

ans = 0

## Supported Functions

The `quaternion` class lets you effectively describe rotations and orientations in MATLAB. The full list of quaternion-supported functions can be found with the `methods` function

```
methods('quaternion')
```

Methods for class quaternion: cat ismatrix power classUnderlying isnan prod compact isrow quaternion conj isscalar rdivide ctranspose isvector reshape disp ldivide rotateframe dist length rotatepoint double log rotmat eq meanrot rotvec euler minus rotvecd eulerd mtimes single exp ndims size horzcat ne slerp iscolumn norm times isempty normalize transpose isequal numel uminus isequaln parts validateattributes isfinite permute vertcat isinf plus Static methods: ones zeros