Solving nonlinear equations for yaw/pitch/roll given rotor/quaternio

  • Thread starter chogg
  • Start date
  • Tags
    Nonlinear
In summary, This conversation is about solving a system of equations involving rotations in 3D space. The equations involve components of a rotor and half-angles of rotation, and are not independent. Several approaches are discussed, but the most successful involves combining equations and using trigonometric addition formulas. The final solution involves explicit formulas for the angles in terms of the components of the rotor. The solution was inspired by considering rotated bivectors and their components.
  • #1
chogg
129
10
I've been doing linear algebra for so long, that I've become quite a dunce at solving nonlinear systems of equations.

tl;dr: Can anyone suggest a fruitful plan of attack for the following system of equations?

[tex]
\begin{align}
\cos\phi_1 \cos\phi_2 \cos\phi_3 + \sigma \sin\phi_1 \sin\phi_2 \sin\phi_3 = {}& K_0 \\
\sin\phi_1 \cos\phi_2 \cos\phi_3 - \sigma \cos\phi_1 \sin\phi_2 \sin\phi_3 = {}& K_1 \\
\cos\phi_1 \sin\phi_2 \cos\phi_3 + \sigma \sin\phi_1 \cos\phi_2 \sin\phi_3 = {}& K_2 \\
\cos\phi_1 \cos\phi_2 \sin\phi_3 - \sigma \sin\phi_1 \sin\phi_2 \cos\phi_3 = {}& K_3
\end{align}
[/tex]

This is 4 equations in 3 unknowns, but they are not independent; it turns out that [itex]K_0^2 + K_1^2 + K_2^2 + K_3^2 = 1[/itex] (as you can easily verify).

Details below...


The motivating problem: I've applied three consecutive rotations in 3D; the planes of these rotations are mutually orthogonal. These equations give the components of the rotor ([itex]K_0, K_1, K_2, K_3[/itex]) in terms of the half-angles of rotation ([itex]\phi_i, \phi_2, \phi_3[/itex]). [itex]\sigma = \pm 1[/itex] is a constant which specifies the handedness of the bivector triple. (I wanted to be general, but at this point I'd accept a method which just picks a convenient handedness.)

Below, I'll list the approaches I've tried in case anyone's interested. I just wanted to put the tl;dr version up at the top.

I'm aware that solutions exist online, but I don't find them satisfying because they don't tell me how to solve something like this. (At least, the ones I've seen.) And I'm taking this as an opportunity to brush up some rusty skills.

Approach 1: Squaring and canceling

I thought it might be helpful to square the equations. That way, I could consider [itex]S_i \equiv \sin^2(\phi_i)[/itex] as my unknowns, replace [itex]\cos^2(\phi_i)[/itex] with [itex](1 - S_i)[/itex], and forget about the trig for a while. There are those pesky linear terms, but these equations have a very specific structure which helps: the linear term is always [itex]\pm 2 \sigma \cos\phi_1 \cos\phi_2 \cos\phi_3 \sin\phi_1 \sin\phi_2 \sin\phi_3 [/itex]. So we can cancel it out and we're left with only squared trigonometric functions.

Unfortunately, the remaining three equations are not independent. No matter how I combine them, all the variables always drop out and I'm left with [itex]\sum K_i^2 = 1[/itex], which I already knew.

Approach 2: Adding equations; using trig addition formulae

If I add the equations for [itex]K_1[/itex] and [itex]K_3[/itex], and also the equations for [itex]K_0[/itex] and [itex]K_2[/itex], I get the following:

[tex]
\begin{align}
\sin(\phi_1 + \phi_3)(\cos\phi_2 - \sigma \sin\phi_2) = {}& K_1 + K_3 \\
\cos(\phi_1 - \sigma\phi_3)(\cos\phi_2 + \sin\phi_2) = {}& K_0 + K_2
\end{align}
[/tex]

If I bite the bullet and pick [itex]\sigma = -1[/itex] (giving up for now on my general solution), these two equations divide quite nicely to give
[tex]
\tan(\phi_1 + \phi_3) = \frac{K_1 + K_3}{K_0 + K_2}
[/tex]

This looks pretty promising! I can take the [itex]\arctan[/itex] of both sides to get a linear equation in [itex]\phi_1[/itex] and [itex]\phi_3[/itex]. If I get two more equations like this, I'll have a linear system -- and there are two more ways to combine these four equations!

Unfortunately, those other two ways don't look very fruitful to me. Even with the same choice of [itex]\sigma = -1[/itex], I get:
[tex]
\begin{align}
\cos\phi_1 \sin(\phi_3 + \phi_2) - \sin\phi_1\sin(\phi_3 - \phi_2) = {}& K_2 + K_3 \\
\cos\phi_1 \cos(\phi_3 - \phi_2) + \sin\phi_1\cos(\phi_3 + \phi_2) = {}& K_0 + K_1
\end{align}
[/tex]
It's just not clear to me how I would change these two equations into a linear equation for [itex]\phi_2[/itex] and [itex]\phi_3[/itex].

Other ideas?

I'd really appreciate any guidance. I've been somewhat obsessing over this problem. :)
 
Physics news on Phys.org
  • #2
Here are the magic combinations of the [itex]K[/itex]'s:

[tex]
\begin{align}
\cos\theta_2 \sin\theta_1 =& 2(K_0 K_1 + \sigma K_2 K_3) \\
\cos\theta_2 \cos\theta_1 =& K_0^2 - K_1^2 - K_2^2 + K_3^2 \\
\sin\theta_2 =& 2(K_0 K_2 - \sigma K_1 K_3) \\
\cos\theta_2 \sin\theta_3 =& 2(K_0 K_3 + \sigma K_2 K_1) \\
\cos\theta_2 \cos\theta_3 =& K_0^2 + K_1^2 - K_2^2 - K_3^2
\end{align}
[/tex]

If we constrain [itex]\theta_2[/itex] to [itex](-\pi, \pi)[/itex], then [itex]\sin\theta_2[/itex] determines it uniquely. And this is a reasonable approach, since allowing higher angles would only lead to redundancy anyway. The other angles are fully determined by the signs of [itex]\sin\theta_i[/itex] and [itex]\cos\theta_i[/itex] as long as [itex]\cos\theta_2 \ne 0[/itex] (a special case). This leaves us with the following explicit solutions for the angles:

[tex]
\begin{align}
\theta_1 &= \text{atan2}(2(K_0 K_1 + \sigma K_2 K_3),
K_0^2 - K_1^2 - K_2^2 + K_3^2) \\
\theta_2 &= \arcsin(2(K_0 K_2 - \sigma K_1 K_3)) \\
\theta_3 &= \text{atan2}(2(K_0 K_3 + \sigma K_2 K_1),
K_0^2 + K_1^2 - K_2^2 - K_3^2)
\end{align}
[/tex]

Inspiration came from considering the rotated bivectors. Note that the first rotation leaves its own bivector unchanged. So, consider the components of that bivector after the full rotation -- this gives 3 equations, which can only depend on the second two angles (greatly simplifying the equations). Each other rotated bivector yielded one useful equation, for the total of 5 [itex]K[/itex]-combinations I listed at the beginning of this post.

I didn't end up learning any general techniques for attacking nonlinear equations, but I don't mind, since this problem is chock-full of beautiful symmetries.
 

1. How do I solve a nonlinear equation for yaw/pitch/roll given rotor/quaternion?

The first step in solving a nonlinear equation for yaw/pitch/roll given rotor/quaternion is to understand the basic principles of quaternions and their relationship to rotations. Then, you can use the appropriate mathematical techniques, such as Newton's method or gradient descent, to iteratively solve the equation and find the values for yaw, pitch, and roll.

2. What are the applications of solving nonlinear equations for yaw/pitch/roll given rotor/quaternion?

Solving nonlinear equations for yaw/pitch/roll given rotor/quaternion has various applications in fields such as robotics, computer graphics, and aerospace engineering. This technique is used to calculate the orientation and movement of objects in 3D space, which is crucial for tasks such as flight control, animation, and object tracking.

3. What are some challenges in solving nonlinear equations for yaw/pitch/roll given rotor/quaternion?

Solving nonlinear equations for yaw/pitch/roll given rotor/quaternion can be challenging due to the complexity of the equations and the need for specialized mathematical knowledge. Additionally, the presence of multiple solutions and the non-convex nature of the problem can make it difficult to find the optimal solution.

4. Is there any software or tools available for solving nonlinear equations for yaw/pitch/roll given rotor/quaternion?

Yes, there are various software packages and libraries available that can assist in solving nonlinear equations for yaw/pitch/roll given rotor/quaternion. Some examples include MATLAB, Mathematica, and the Robotics Toolbox for MATLAB. Additionally, many programming languages, such as Python and C++, have libraries specifically designed for solving quaternion-related problems.

5. How can I verify the accuracy of the solutions obtained from solving nonlinear equations for yaw/pitch/roll given rotor/quaternion?

To verify the accuracy of the solutions obtained, you can compare the results with known solutions or use techniques such as error analysis to evaluate the deviation from the expected values. Additionally, it is crucial to check for any physical constraints and limitations that may affect the accuracy of the solutions.

Similar threads

  • Linear and Abstract Algebra
Replies
34
Views
2K
  • Linear and Abstract Algebra
Replies
4
Views
1K
  • Linear and Abstract Algebra
Replies
3
Views
933
  • Advanced Physics Homework Help
Replies
2
Views
1K
  • Advanced Physics Homework Help
Replies
1
Views
2K
  • Calculus and Beyond Homework Help
Replies
1
Views
767
  • Quantum Physics
Replies
2
Views
1K
  • Advanced Physics Homework Help
Replies
2
Views
981
  • Linear and Abstract Algebra
Replies
4
Views
972
  • Engineering and Comp Sci Homework Help
Replies
33
Views
3K
Back
Top