如何插值旋转? [英] How to interpolate rotations?

问题描述

我有两个描述旋转的向量；开始旋转A和目标旋转B.如何最好地将因子A插值A逼近B?

I have two vectors describing rotations; a start rotation A and a target rotation B. How would I best go about interpolating A by a factor F to approach B?

当需要内插多个维度(即产生不希望的旋转)时，对向量使用简单的lerp无效.也许可以根据旋转向量构建四元数并使用slerp.但是，如何才能从生成的四元数中提取一个描述新旋转的矢量?

Using a simple lerp on the vectors fails to work when more than one dimension needs to be interpolated (i.e. produces undesirable rotations). Maybe building quaternions from the rotation vectors and using slerp is the way to go. But how, then, could I extract a vector describing the new rotation from the resulting quaternion?

谢谢.

推荐答案

由于我似乎不太了解您的问题，因此这里有一些

Since I don't seem to understand your question, here is a little SLERP implementation in python using numpy. I plotted the results using matplotlib (v.99 for Axes3D). I don't know if you can use python, but does look like your SLERP implementation? It seems to me to give fine results ...

from numpy import *
from numpy.linalg import norm

def slerp(p0, p1, t):
        omega = arccos(dot(p0/norm(p0), p1/norm(p1)))
        so = sin(omega)
        return sin((1.0-t)*omega) / so * p0 + sin(t*omega)/so * p1


# test code
if __name__ == '__main__':
    pA = array([-2.0, 0.0, 2.0])
    pB = array([0.0, 2.0, -2.0])

    ps = array([slerp(pA, pB, t) for t in arange(0.0, 1.0, 0.01)])

    from pylab import *
    from mpl_toolkits.mplot3d import Axes3D
    f = figure()
    ax = Axes3D(f)
    ax.plot3D(ps[:,0], ps[:,1], ps[:,2], '.')
    show()

这篇关于如何插值旋转?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！