Exploring Rotation Matrices: Finite & Infinitesimal Rotations

In summary, the conversation discusses rotating by 90* about the x-axis and then 90* about the y-axis, resulting in a non-commutative rotation matrix. It also touches on the possibility of commutativity for infinitesimal rotations and provides the rotation matrices for x,y,z axes.
  • #1
neelakash
511
1

Homework Statement



Can anyone help me to proceed with this?

If we execute rotations of 90* about x-axis and 90* about y axis-what is the resulatant rotation matrix?Will the result commute if we rotate by changing the order?Will they commute if infinitesimal rotations are considered?

Homework Equations


The Attempt at a Solution




A qualitative thinking suggest that they will not commute for finite angle but may commute for infinitesimal angles...
...But I possibly cannot visualise the picture correctly.Can anyone refer to some picture?

Most importantly,how to proceed with the calculations?

By the way,what is the rotation matrix for rotation about x,y,z axes?
 
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  • #2



Hello,

To answer your first question, the resultant rotation matrix for rotating 90* about the x-axis and then 90* about the y-axis would be:

R = [0 -1 0; 1 0 0; 0 0 1]

This can be derived by multiplying the individual rotation matrices for each axis:

Rx = [1 0 0; 0 0 -1; 0 1 0] and Ry = [0 0 1; 0 1 0; -1 0 0]

Rx*Ry = [0 -1 0; 1 0 0; 0 0 1]

To answer your second question, the order of rotation does matter in this case. If you change the order to rotating 90* about the y-axis and then 90* about the x-axis, the resultant rotation matrix would be:

R = [0 1 0; -1 0 0; 0 0 1]

This is not the same as the previous result and therefore, they do not commute.

For infinitesimal rotations, the result may or may not commute depending on the specific angles chosen.

To visualize the rotation, you can imagine a 3D coordinate system with a point at (1,0,0). After rotating 90* about the x-axis, the point would be at (1,0,-1). Then, rotating 90* about the y-axis would bring the point to (0,0,-1).

The rotation matrices for rotating about the x,y,z axes are:

Rx = [1 0 0; 0 cos(theta) -sin(theta); 0 sin(theta) cos(theta)]

Ry = [cos(theta) 0 sin(theta); 0 1 0; -sin(theta) 0 cos(theta)]

Rz = [cos(theta) -sin(theta) 0; sin(theta) cos(theta) 0; 0 0 1]

I hope this helps you with your calculations and understanding of rotations. Let me know if you have any further questions. Good luck!
 

1. What are rotation matrices and how are they used in science?

Rotation matrices are mathematical tools used to describe and analyze the rotation of objects in space. They are commonly used in physics, engineering, and computer graphics to represent and manipulate 3D rotations. They are also used in robotics for motion planning and control.

2. What is the difference between finite and infinitesimal rotations?

Finite rotations are rotations that involve a change in orientation and can be described by a rotation matrix. Infinitesimal rotations, on the other hand, are very small rotations that are often used in mathematical models to simplify calculations. They are represented by infinitesimal rotation matrices, which are essentially the derivative of a finite rotation matrix.

3. Can any object be rotated using a rotation matrix?

Yes, any object with a defined orientation in space can be rotated using a rotation matrix. This includes both 2D and 3D objects, as well as objects with complex shapes and orientations.

4. How are rotation matrices calculated and what do they represent?

Rotation matrices are calculated using trigonometric functions and linear algebra. They represent the transformation of a coordinate system from one orientation to another. Each element in a rotation matrix represents the cosine or sine of an angle of rotation around a specific axis.

5. What are some real-world applications of rotation matrices?

Rotation matrices have numerous applications in science and technology. Some examples include spacecraft navigation, computer animation, robotics, and crystallography. They are also used in medical imaging, such as MRI scans, to analyze the orientation of tissues and structures in the body.

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