Building a rotational matrix transformation

In summary, the conversation discusses the building of rotational transformation matrices for both counterclockwise and clockwise angles. The speaker realizes that they do not need separate matrices for each direction as clockwise rotation is equivalent to counterclockwise rotation with a negative angle. This is due to the properties of cosine and sine functions. The importance of this concept is highlighted by the fact that rotating clockwise and then counterclockwise (or vice versa) by the same angle results in returning to the original position.
  • #1
adrs
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0
I am trying to build a rotational transformation matrix both for counterclockwise and clockwise angles.

The first matrix in the picture is for counterclockwise angles and the second one for clockwise angles. The first matrix I built corresponds to the one given in my linear algebra book so it seems the building process's OK.
However, in my book there isn't one for clockwise angles and that's why I've built one. I've been searching on the Internet and it seems that the rotational matrix for clockwise angles is the same as the one for counterclokwise ones but with the sines with opposite signs.
Nevertheless, that's not the one I've obtained If I thry for example with a 24.78 clokwise angle.

So, where does my reasoning fail? Thanks!
 

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  • #2
You don't really need different matrices for "clockwise" and "counterclockwise" rotattions because rotation "clockwise" is just the same as rotation counterclockwise but with negative angle.

Rotation through angle [itex]\theta[/itex], counterclockwise, is given, as you say, by the matrix
[tex]\begin{bmatrix}cos(\theta) & -sin(\theta) \\ sin(\theta) & cos(\theta) \end{bmatrix}[/tex]

so that rotation through the same angle, clockwise is the same thing with [itex]\theta[/itex] replaced by [itex]-\theta[/itex]:
[tex]\begin{bmatrix}cos(-\theta) & -sin(-\theta) \\ sin(-\theta) & cos(-\theta) \end{bmatrix}[/tex]

Perhaps what you are missing is that cosine is an even function and sine is an odd function: [itex]cos(-\theta)= cos(\theta)[/itex] and [itex]sin(-\theta)= -sin(\theta)[/itex] so that the previous matrix is just
[tex]\begin{bmatrix}cos(\theta) & sin(\theta) \\ -sin(\theta) & cos(\theta) \end{bmatrix}[/tex]
the "transpose" of the counterclockwise rotation.

Of course, rotating cockwise by a given angle and then counterclockwise by the same angle, or vice-versa, gets you right back to where you were before so a good exercise is to do the two multiplications
[tex]\begin{bmatrix}cos(\theta) & -sin(\theta) \\ sin(\theta) & cos(\theta) \end{bmatrix}\begin{bmatrix}cos(\theta) & sin(\theta) \\ -sin(\theta) & cos(\theta)\end{bmatrix}[/tex]
and
[tex]\begin{bmatrix}cos(\theta) & sin(\theta) \\ -sin(\theta) & cos(\theta) \end{bmatrix}\begin{bmatrix}cos(\theta) & -sin(\theta) \\ sin(\theta) & cos(\theta)\end{bmatrix}[/tex]
and show that they both give the identity matrix.
 

Related to Building a rotational matrix transformation

1. What is a rotational matrix transformation?

A rotational matrix transformation is a mathematical operation that involves rotating a coordinate system around an axis to change the orientation of the coordinate axes. This is typically represented by a 3x3 matrix and is used in various fields of science and engineering, such as computer graphics and robotics.

2. How is a rotational matrix transformation calculated?

A rotational matrix transformation can be calculated using a set of equations that involve the angle of rotation and the coordinates of the axis of rotation. The specific equations used will depend on the type of rotation (e.g. 2D or 3D) and the direction of rotation (clockwise or counterclockwise).

3. What are the applications of rotational matrix transformations?

Rotational matrix transformations have many applications, including computer graphics (e.g. rotating objects in 3D space), robotics (e.g. rotating joints of a robot arm), and physics (e.g. calculating the angular momentum of a rotating object).

4. What are the properties of a rotational matrix transformation?

Some important properties of rotational matrix transformations include orthogonality (the columns and rows of the matrix are perpendicular to each other), preserving angles and distances, and having a determinant of 1 (for 2D transformations) or -1 (for 3D transformations).

5. How is a rotational matrix transformation different from other types of transformations?

A rotational matrix transformation is different from other types of transformations, such as translation or scaling, in that it involves rotating the coordinate system as a whole, rather than moving or resizing individual points or objects within the coordinate system. It is also different from other types of transformations, such as shearing or reflection, in that it does not distort or flip the coordinate system.

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