Fastest interpolation method for attitude quaternions?

In summary, the conversation discusses the use of interpolation methods, specifically least-squares fitting using a polynomial, to calculate the rotation of a spacecraft relative to a fixed frame. The individual examines the accuracy and computation time of different interpolation methods, including Spherical Linear Interpolation, Spherical Cubic Interpolation, and Spline Interpolation. The main goals of trying out these methods are precision and minimizing computation time.
  • #1
vicjun
18
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I hesitated between posting this in the Mathematics forum or here, but since it's fairly applied, I chose this place. Sorry if it should've gone somewhere else.

I posted another thread earlier (https://www.physicsforums.com/showthread.php?t=599737), about having trouble finding the quaternion derivative from the quaternion and the angular velocity. That problem is now resolved. I mentioned that I interpolate the quaternion derivatives to find a continuous function.

The interpolation method used is least-squares fitting using a n-degree polynomial (n varies between 3 and 7, this is determined automatically), resulting in four n-degree polynomials, one for each quaternion component. This works fine.

I estimated the error in the interpolation by resampling (using the polynomials above) the quaternion component derivatives at the same dates used for the interpolation, and then calculating the angle between a quaternion derivative before and after interpolation. It is in the order of 10-5 radians. Is this a correct method of estimating the error or is there a better way?

I would also like the explore other interpolation methods, that are perhaps more suited for quaternions. The point of all this is to calculate the rotation of a spacecraft (i.e., a body-fixed frame) relative a fixed frame (in this case the local orbital frame). I found a document (http://www.geometrictools.com/Documentation/Quaternions.pdf) detailing three other methods: Spherical Linear Interpolation, Spherical Cubic Interpolation and Spline Interpolation. Are these better for interpolating quaternions? If yes, then why?

The goals of trying out other interpolation methods are mainly:

1. Precision (minimizing the interpolation error)
2. Minimizing computation time


Thanks in advance!

vicjun
 
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  • #2
It is not quite clear to me what you mean by interpolating quaternions. The algorithms you've found are quite interesting, but I'm afraid we need a better described problem statement and then individual examinations of the different methods. I doubt that there is already a ready-made answer. Sometimes there is simply work to do.
 

What is the purpose of interpolation in attitude quaternions?

The purpose of interpolation in attitude quaternions is to find a smooth and continuous path between two given orientations. This is particularly useful in motion tracking and animation applications where a smooth transition between orientations is desired.

What are the advantages of using the fastest interpolation method for attitude quaternions?

The fastest interpolation method for attitude quaternions is advantageous because it allows for efficient computation and minimizes errors in the resulting interpolation. It also provides a more accurate representation of the true path between orientations.

How does the fastest interpolation method for attitude quaternions work?

The fastest interpolation method for attitude quaternions works by using a mathematical formula that calculates the shortest path between two quaternions. This path is then divided into smaller segments, and the attitude quaternions are interpolated at each segment to create a smooth transition.

What factors should be considered when choosing an interpolation method for attitude quaternions?

When choosing an interpolation method for attitude quaternions, it is important to consider the accuracy, efficiency, and computational complexity of the method. Additionally, the type of data being interpolated and the desired smoothness of the resulting path should also be taken into account.

Are there any limitations to using the fastest interpolation method for attitude quaternions?

While the fastest interpolation method for attitude quaternions is efficient and accurate, it may not always be the best choice for all types of data and applications. It is important to consider the specific needs and requirements of each project before deciding on an interpolation method.

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