Composition of Quaternions as rotations

In summary, the conversation discusses the difficulty in finding the single quaternion rotation that can be used to rotate a vector from (1,1,0) to (0,1,1). The attempt at solving this involves using the composition of rotations in reverse order. The final solution is a rotation of 90 degrees about the y-axis, represented by the quaternion form r = cos45+jsin45. However, some confusion arises when trying to interpret this solution geometrically.
  • #1
tomelwood
34
0

Homework Statement


Hi, I am having problems in showing that in practise the composition of two rotations represented by quaternions is still a rotation.
The example I have constructed is:
Rotate (1,1,0) by 45 degrees about the z axis.
The quaternion to use is thus q = cos(22.5)+ksin(22.5)
This gives the vector (0,√2,0), as one would expect.
Then, rotate this new vector by 45 degrees about the x acis.
The quaternion to use is thus p = cos(22.5)+isin(22.5)
This gives the vector (0,1,1), as expected.
However, trying to find the single quaternion rotation to get from (1,1,0) to (0,1,1) is proving problematic..

Homework Equations


I know that composition of rotations is done in reverse order, ie to find the single quaternion that I need to use, I need to do pq and then apply this to (1,1,0) to give me (0,1,1)

The Attempt at a Solution


Now, I know that the answer is a rotation of 90 degrees about the y-axis, ie about (0,1,0), which is, in quaternion form, r = cos45+jsin45

But when I multiply p with q, I do not get this.
In fact, pq= cos^2(22.5) + isin(22.5)cos(22.5) + ksin(22.5)cos(22.5) - jsin^2(22.5)
which I cannot get to equal what I want!

By adding and subtracting another sin^2 , I can get the cos45, but then I am left with
sin(22.5)(icos(22.5)+kcos(22.5)-jsin(22.5)) which is no closer!

Could somebody please explain where I have gone wrong/what identities I have missed, as this should work, and I don't understand why it isn't!

Many thanks.
 
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  • #2
Having investigated further, I have found that multiplying (1,1,0) by that quaternion that I didn't like does actually give (0,1,1) , but I don't understand how I can interpret that geometrically - ie about what axis and by what angle is the rotation being performed?
Because the usual way of writing that is in the form
cos(θ/2)+Asin(θ/2) , where θ is the angle of rotation and A is the unit vector which is the axis of rotation...
Unless, I write it out numerically:
0.85355+0.35355i-0.14644j+0.35355k
Therefore the angle of rotation is 2arccos(0.85355) = 62.8 degrees
And the axis of rotation is the vector (0.35355, -0.14644, 0.35355) But this isn't a unit vector...

Am I any closer?
 

1. What are quaternions and how are they used in rotations?

Quaternions are a mathematical concept used to represent rotations in three-dimensional space. They are an extension of complex numbers and can be expressed as a combination of a scalar (real) part and a vector (imaginary) part.

2. How are quaternions multiplied and how does it relate to composition of rotations?

To multiply two quaternions, the rules of quaternion multiplication are used. This includes multiplying the scalar parts and adding the cross product of the vector parts. The result of quaternion multiplication is a new quaternion that represents the composition of the two rotations.

3. What is the difference between a single quaternion and a sequence of quaternions?

A single quaternion represents a single rotation in three-dimensional space, while a sequence of quaternions represents a series of rotations that can be combined to create a final rotation. This allows for more complex rotations to be represented.

4. Can quaternions be used to represent any rotation in three-dimensional space?

Yes, quaternions can represent any rotation in three-dimensional space. This is because they have four degrees of freedom, which is enough to capture all possible rotations in three dimensions.

5. How are quaternions used in computer graphics and animation?

Quaternions are commonly used in computer graphics and animation to represent rotations. They are more efficient and stable than other methods, such as Euler angles, and allow for smooth interpolation between rotations, resulting in more realistic and fluid animations.

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