So, imagine my situation. I need to handle rotation conversions in Python with no prior knowledge of the subject. I stumbled upon the scipy.spatial.transform.Rotation class and thought "Neat! That is all taken care of for me!". But as I did a few tests with the conversions I noticed something odd. When I take a random quaternion and convert it to a rotation matrix and back, the new quaternion is completely different from the original one, like beyond any plausible rounding errors.
Can anybody explain this difference?
Code:
from scipy.spatial.transform import Rotation as R
quat = [0.40, 0.27, 0.29, 0.14]
print("\nOriginal Quaternion")
print(quat)
matrix_from_quat = R.from_quat(quat).as_matrix()
print("\nMatrix from Quaternion")
print(matrix_from_quat)
quat_from_matrix = R.from_matrix(matrix_from_quat).as_quat()
print("\nQuaternion from Matrix")
print(quat_from_matrix)
Output:
Original Quaternion
[0.4, 0.27, 0.29, 0.14]
Matrix from Quaternion
[[ 0.06714201 0.40047534 0.91384433]
[ 0.88294712 -0.45038622 0.13250149]
[ 0.46464646 0.7979798 -0.38383838]]
Quaternion from Matrix
[0.68945025 0.46537892 0.49985143 0.24130759]
