Several methods to describe orientations of a rigid body in three dimensions have been developed. They are summarized in the following sections.
Euler angles The first attempt to represent an orientation is attributed to
Leonhard Euler. He imagined three reference frames that could rotate one around the other, and realized that by starting with a fixed reference frame and performing three rotations, he could get any other reference frame in the space (using two rotations to fix the vertical axis and another to fix the other two axes). The values of these three rotations are called
Euler angles.
Tait–Bryan angles These are three angles, also known as yaw, pitch and roll, Navigation angles and Cardan angles. Mathematically they constitute a set of six possibilities inside the twelve possible sets of Euler angles, the ordering being the one best used for describing the orientation of a vehicle such as an airplane. In aerospace engineering they are usually referred to as Euler angles.
Orientation vector Euler also realized that the composition of two rotations is equivalent to a single rotation about a different fixed axis (
Euler's rotation theorem). Therefore, the composition of the former three angles has to be equal to only one rotation, whose axis was complicated to calculate until matrices were developed. Based on this fact he introduced a vectorial way to describe any rotation, with a vector on the rotation axis and module equal to the value of the angle. Therefore, any orientation can be represented by a rotation vector (also called Euler vector) that leads to it from the reference frame. When used to represent an orientation, the rotation vector is commonly called orientation vector, or attitude vector. A similar method, called
axis–angle representation, describes a rotation or orientation using a
unit vector aligned with the rotation axis, and a separate value to indicate the angle (see figure).
Orientation matrix With the introduction of matrices, the Euler theorems were rewritten. The rotations were described by
orthogonal matrices referred to as rotation matrices or direction cosine matrices. When used to represent an orientation, a rotation matrix is commonly called orientation matrix, or attitude matrix. The above-mentioned Euler vector is the
eigenvector of a rotation matrix (a rotation matrix has a unique real
eigenvalue). The product of two rotation matrices is the composition of rotations. Therefore, as before, the orientation can be given as the rotation from the initial frame to achieve the frame that we want to describe. The
configuration space of a non-
symmetrical object in
n-dimensional space is
SO(n) × Rn. Orientation may be visualized by attaching a basis of
tangent vectors to an object. The direction in which each vector points determines its orientation.
Orientation quaternion Another way to describe rotations is using
rotation quaternions, also called versors. They are equivalent to rotation matrices and rotation vectors. With respect to rotation vectors, they can be more easily converted to and from matrices. When used to represent orientations, rotation quaternions are typically called orientation quaternions or attitude quaternions. == Usage examples ==