Singularity also with Euler-Rodrigues parametrisation?

In summary, the conversation discusses the development of a multibody dynamics software using the Lagrangian equations approach and the Euler-Rodrigues parametrisation for 3D rotation. Concerns are raised about the singularity of the parametrisation for rotations greater than π and a reference is provided for a potential solution.
  • #1
TGVF
6
2
Hello,
Trying to develop a multibody dynamics software of my own (just to understand the nitty-gritty details of such stuff), I chose the Lagrangian equations approach, with the Euler-Rodrigues parametrisation (quaternion) for 3D rotation as it is supposed to remove the gimbal locking singularity of conventional Euler angles. When angular position is to be part of the generalized coordinates, I take b, c and d and leave a as a dependant variable computed from the normalisation condition: ##a^2= b^2+c^2+d^2 ## . I take the positive value of a, by convention. Sounds good but... The 3x3 transformation from angular velocity vector ## \begin{pmatrix} u \\ v \\ w \end{pmatrix} ## to vector ## \begin{pmatrix} \dot b \\ \dot c \\ \dot d \end{pmatrix} ## is singular for any rotation such that a=0 (determinant is a/8), which a π rd rotation about any axis. This singularity is a potential problem for the calculation of the inverse transform ## \frac {\partial \Omega} {\partial \dot q}## and also ## \frac {\partial^2 \Omega} {\partial \dot q \partial q}## that are necessary for computing the Lagrange equations.
Looks like another sort of gimbal-locking case! Did I miss something :confused: ? Or how to circumvent this problem?
Thanks for any clarification!
 
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  • #2
Evidently you're normalization introduces singularities in the Euler-Rodriguez paramemterization for rotations greater than##\pi## .I suggest you Google: O. Buchan, L. Trained "The Vectorial Paramemterization of Rotation". Try implementing the scheme found in Appendix A.
 
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  • #3
Fred Wright said:
Evidently you're normalization introduces singularities in the Euler-Rodriguez paramemterization for rotations greater than##\pi## .I suggest you Google: O. Buchan, L. Trained "The Vectorial Paramemterization of Rotation". Try implementing the scheme found in Appendix A.
Excellent! I should have spotted this reference before posting since I know some other publications of Olivier Bauchau (relevant to non linear elasticity modelling of slender beams).
Thanks a lot for support!
 

Related to Singularity also with Euler-Rodrigues parametrisation?

1. What is the "Singularity" in Euler-Rodrigues parametrisation?

The "Singularity" in Euler-Rodrigues parametrisation refers to the point at which the rotation matrix being represented becomes undefined. This happens when the angle of rotation approaches 180 degrees, causing the matrix to become singular.

2. How is Euler-Rodrigues parametrisation different from other rotation representations?

Euler-Rodrigues parametrisation is a method for representing rotations in three-dimensional space using a vector and an angle. It differs from other methods, such as Euler angles or quaternions, in that it avoids the issue of gimbal lock and has a more intuitive geometric interpretation.

3. What is the advantage of using Euler-Rodrigues parametrisation?

Euler-Rodrigues parametrisation has the advantage of being able to represent any rotation in three-dimensional space with a single vector and angle, making it a more compact representation than other methods. It also has a more intuitive geometric interpretation, making it easier to visualize and understand.

4. Can Euler-Rodrigues parametrisation be used for all types of rotations?

Yes, Euler-Rodrigues parametrisation can be used for any type of rotation in three-dimensional space, including rotations around any axis and multiple rotations around different axes. However, as mentioned before, it becomes singular when the angle of rotation approaches 180 degrees.

5. How is the Euler-Rodrigues parametrisation calculated?

The Euler-Rodrigues parametrisation is calculated by converting the rotation matrix into a quaternion, and then extracting the vector and angle parameters from the quaternion. This can also be done in reverse to convert back to a rotation matrix.

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