Rodrigues' rotation formula

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In the theory of three-dimensional rotation, Rodrigues' rotation formula, named after Olinde Rodrigues, is an efficient algorithm for rotating a vector in space, given an axis and angle of rotation. By extension, this can be used to transform all three basis vectors to compute a rotation matrix in SO(3), the group of all rotation matrices, from an axis–angle representation. In other words, the Rodrigues' formula provides an algorithm to compute the exponential map from so(3), the Lie algebra of SO(3), to SO(3) without actually computing the full matrix exponential.

Statement[]

If v is a vector in ℝ³ and k is a unit vector describing an axis of rotation about which v rotates by an angle θ according to the right hand rule, the Rodrigues formula for the rotated vector v_rot is

The intuition of the above formula is that the first term scales the vector down, while the second skews it (via vector addition) toward the new rotational position. The third term re-adds the height (relative to ${\displaystyle {\textbf {k}}}$) that was lost by the first term.

An alternative statement is to write the axis vector as a cross product a × b of any two nonzero vectors a and b which define the plane of rotation, and the sense of the angle θ is measured away from a and towards b. Letting α denote the angle between these vectors, the two angles θ and α are not necessarily equal, but they are measured in the same sense. Then the unit axis vector can be written

${\displaystyle \mathbf {k} ={\frac {\mathbf {a} \times \mathbf {b} }{|\mathbf {a} \times \mathbf {b} |}}={\frac {\mathbf {a} \times \mathbf {b} }{|\mathbf {a} ||\mathbf {b} |\sin \alpha }}\,.}$

This form may be more useful when two vectors defining a plane are involved. An example in physics is the Thomas precession which includes the rotation given by Rodrigues' formula, in terms of two non-collinear boost velocities, and the axis of rotation is perpendicular to their plane.

Derivation[]

Rodrigues' rotation formula rotates v by an angle θ around vector k by decomposing it into its components parallel and perpendicular to k, and rotating only the perpendicular component.

Vector geometry of Rodrigues' rotation formula, as well as the decomposition into parallel and perpendicular components.

Let k be a unit vector defining a rotation axis, and let v be any vector to rotate about k by angle θ (right hand rule, anticlockwise in the figure).

Using the dot and cross products, the vector v can be decomposed into components parallel and perpendicular to the axis k,

${\displaystyle \mathbf {v} =\mathbf {v} _{\parallel }+\mathbf {v} _{\perp }\,,}$

where the component parallel to k is

${\displaystyle \mathbf {v} _{\parallel }=(\mathbf {v} \cdot \mathbf {k} )\mathbf {k} }$

called the vector projection of v on k, and the component perpendicular to k is

${\displaystyle \mathbf {v} _{\perp }=\mathbf {v} -\mathbf {v} _{\parallel }=\mathbf {v} -(\mathbf {k} \cdot \mathbf {v} )\mathbf {k} =-\mathbf {k} \times (\mathbf {k} \times \mathbf {v} )}$

called the vector rejection of v from k.

The vector k × v can be viewed as a copy of v_⊥ rotated anticlockwise by 90° about k, so their magnitudes are equal but directions are perpendicular. Likewise the vector k × (k × v) a copy of v_⊥ rotated anticlockwise through 180° about k, so that k × (k × v) and v_⊥ are equal in magnitude but in opposite directions (i.e. they are negatives of each other, hence the minus sign). Expanding the vector triple product establishes the connection between the parallel and perpendicular components, for reference the formula is a × (b × c) = (a · c)b − (a · b)c given any three vectors a, b, c.

The component parallel to the axis will not change magnitude nor direction under the rotation,

${\displaystyle \mathbf {v} _{\parallel \mathrm {rot} }=\mathbf {v} _{\parallel }\,,}$

only the perpendicular component will change direction but retain its magnitude, according to

${\displaystyle {\begin{aligned}\left|\mathbf {v} _{\perp \mathrm {rot} }\right|&=\left|\mathbf {v} _{\perp }\right|\,,\\\mathbf {v} _{\perp \mathrm {rot} }&=\cos(\theta )\mathbf {v} _{\perp }+\sin(\theta )\mathbf {k} \times \mathbf {v} _{\perp }\,,\end{aligned}}}$

and since k and v_∥ are parallel, their cross product is zero k × v_∥ = 0, so that

${\displaystyle \mathbf {k} \times \mathbf {v} _{\perp }=\mathbf {k} \times \left(\mathbf {v} -\mathbf {v} _{\parallel }\right)=\mathbf {k} \times \mathbf {v} -\mathbf {k} \times \mathbf {v} _{\parallel }=\mathbf {k} \times \mathbf {v} }$

and it follows

${\displaystyle \mathbf {v} _{\perp \mathrm {rot} }=\cos(\theta )\mathbf {v} _{\perp }+\sin(\theta )\mathbf {k} \times \mathbf {v} \,.}$

This rotation is correct since the vectors v_⊥ and k × v have the same length, and k × v is v_⊥ rotated anticlockwise through 90° about k. An appropriate scaling of v_⊥ and k × v using the trigonometric functions sine and cosine gives the rotated perpendicular component. The form of the rotated component is similar to the radial vector in 2D planar polar coordinates (r, θ) in the Cartesian basis

${\displaystyle \mathbf {r} =r\cos(\theta )\mathbf {e} _{x}+r\sin(\theta )\mathbf {e} _{y}\,,}$

where e_x, e_y are unit vectors in their indicated directions.

Now the full rotated vector is

${\displaystyle \mathbf {v} _{\mathrm {rot} }=\mathbf {v} _{\parallel \mathrm {rot} }+\mathbf {v} _{\perp \mathrm {rot} }\,,}$

By substituting the definitions of v_∥rot and v_⊥rot in the equation results in

${\displaystyle {\begin{aligned}\mathbf {v} _{\mathrm {rot} }&=\mathbf {v} _{\parallel }+\cos(\theta )\,\mathbf {v} _{\perp }+\sin(\theta )\,\mathbf {k} \times \mathbf {v} \\&=\mathbf {v} _{\parallel }+\cos(\theta )\left(\mathbf {v} -\mathbf {v} _{\parallel }\right)+\sin(\theta )\,\mathbf {k} \times \mathbf {v} \\&=\cos(\theta )\,\mathbf {v} +(1-\cos \theta )\mathbf {v} _{\parallel }+\sin(\theta )\,\mathbf {k} \times \mathbf {v} \\&=\cos(\theta )\,\mathbf {v} +(1-\cos \theta )(\mathbf {k} \cdot \mathbf {v} )\mathbf {k} +\sin(\theta )\,\mathbf {k} \times \mathbf {v} \end{aligned}}}$

Matrix notation[]

Representing v and k × v as column matrices, the cross product can be expressed as a matrix product

${\displaystyle {\begin{bmatrix}(\mathbf {k} \times \mathbf {v} )_{x}\\(\mathbf {k} \times \mathbf {v} )_{y}\\(\mathbf {k} \times \mathbf {v} )_{z}\end{bmatrix}}={\begin{bmatrix}k_{y}v_{z}-k_{z}v_{y}\\k_{z}v_{x}-k_{x}v_{z}\\k_{x}v_{y}-k_{y}v_{x}\end{bmatrix}}={\begin{bmatrix}0&-k_{z}&k_{y}\\k_{z}&0&-k_{x}\\-k_{y}&k_{x}&0\end{bmatrix}}{\begin{bmatrix}v_{x}\\v_{y}\\v_{z}\end{bmatrix}}\,.}$

Letting K denote the "cross-product matrix" for the unit vector k,

${\displaystyle \mathbf {K} =\left[{\begin{array}{ccc}0&-k_{z}&k_{y}\\k_{z}&0&-k_{x}\\-k_{y}&k_{x}&0\end{array}}\right]\,,}$

that is to say,

${\displaystyle \mathbf {K} \mathbf {v} =\mathbf {k} \times \mathbf {v} }$

for any vector v. (In fact, K is the unique matrix with this property. It has eigenvalues 0 and ±i).

It follows that iterating the cross product is equivalent to multiplying by the cross-product matrix on the left; specifically:

${\displaystyle \mathbf {K} (\mathbf {K} \mathbf {v} )=\mathbf {K} ^{2}\mathbf {v} =\mathbf {k} \times (\mathbf {k} \times \mathbf {v} )\,.}$

The previous rotation formula in matrix language is therefore

${\displaystyle {\begin{aligned}\mathbf {v} _{\mathrm {rot} }&=\mathbf {v} \cos \theta +(\mathbf {k} \times \mathbf {v} )\sin \theta +\mathbf {k} ~(\mathbf {k} \cdot \mathbf {v} )(1-\cos \theta )\\&=\mathbf {v} \cos \theta +(\mathbf {k} \times \mathbf {v} )\sin \theta +(\mathbf {v} -\mathbf {v} _{\perp })(1-\cos \theta )\\&=\mathbf {v} \cos \theta +(\mathbf {k} \times \mathbf {v} )\sin \theta +(\mathbf {v} +\mathbf {k} \times (\mathbf {k} \times \mathbf {v} ))(1-\cos \theta )\\&=\mathbf {v} \cos \theta +(\mathbf {k} \times \mathbf {v} )\sin \theta +(\mathbf {v} +\mathbf {K} (\mathbf {K} \mathbf {v} ))(1-\cos \theta )\\&=\mathbf {v} (\cos \theta +1-\cos \theta )+(\mathbf {k} \times \mathbf {v} )\sin \theta +\mathbf {K} (\mathbf {K} \mathbf {v} )(1-\cos \theta )\end{aligned}}}$

So we have:

${\displaystyle \mathbf {v} _{\mathrm {rot} }=\mathbf {v} +(\sin \theta )\mathbf {K} \mathbf {v} +(1-\cos \theta )\mathbf {K} ^{2}\mathbf {v} \,,\quad \|\mathbf {K} \|_{2}=1\,.}$

Note the coefficient of the leading term is now 1, in this notation: see the Lie-Group discussion below.

Factorizing the v allows the compact expression

${\displaystyle \mathbf {v} _{\mathrm {rot} }=\mathbf {R} \mathbf {v} }$

where

is the rotation matrix through an angle θ counterclockwise about the axis k, and I the 3 × 3 identity matrix.^[1] This matrix R is an element of the rotation group SO(3) of ℝ³, and K is an element of the Lie algebra ${\displaystyle {\mathfrak {so}}(3)}$ generating that Lie group (note that K is skew-symmetric, which characterizes ${\displaystyle {\mathfrak {so}}(3)}$).

In terms of the matrix exponential,

${\displaystyle \mathbf {R} =\exp(\theta \mathbf {K} )\,.}$

To see that the last identity holds, one notes that

${\displaystyle \mathbf {R} (\theta )\mathbf {R} (\phi )=\mathbf {R} (\theta +\phi ),\quad \mathbf {R} (0)=\mathbf {I} \,,}$

characteristic of a one-parameter subgroup, i.e. exponential, and that the formulas match for infinitesimal θ.

For an alternative derivation based on this exponential relationship, see exponential map from ${\displaystyle {\mathfrak {so}}(3)}$ to SO(3). For the inverse mapping, see log map from SO(3) to ${\displaystyle {\mathfrak {so}}(3)}$.

The Hodge dual of the rotation ${\displaystyle \mathbf {R} }$ is just ${\displaystyle \mathbf {R} ^{*}=-\sin(\theta )\mathbf {k} }$ which enables the extraction of both the axis of rotation and the sine of the angle of the rotation from the rotation matrix itself, with the usual ambiguity,

${\displaystyle {\begin{aligned}\sin(\theta )&=\sigma \left|\mathbf {R} ^{*}\right|\\[3pt]\mathbf {k} &=-{\frac {\sigma \mathbf {R} ^{*}}{\left|\mathbf {R} ^{*}\right|}}\end{aligned}}}$

where ${\displaystyle \sigma =\pm 1}$. The above simple expression results from the fact that the Hodge duals of ${\displaystyle \mathbf {I} }$ and ${\displaystyle \mathbf {K} ^{2}}$ are zero, and ${\displaystyle \mathbf {K} ^{*}=-\mathbf {k} }$.

When applying the Rodrigues' formula, however, the usual ambiguity could be removed with an extended form of the formula.^a

See also[]

• Axis angle
• Rotation (mathematics)
• SO(3) and SO(4)
• Euler–Rodrigues formula

References[]

• Leonhard Euler, "Problema algebraicum ob affectiones prorsus singulares memorabile", Commentatio 407 Indicis Enestoemiani, Novi Comm. Acad. Sci. Petropolitanae 15 (1770), 75–106.
• Olinde Rodrigues, "Des lois géométriques qui régissent les déplacements d'un système solide dans l'espace, et de la variation des coordonnées provenant de ces déplacements considérés indépendants des causes qui peuvent les produire", Journal de Mathématiques Pures et Appliquées 5 (1840), 380–440. online.
• Don Koks, (2006) Explorations in Mathematical Physics, Springer Science+Business Media,LLC. ISBN 0-387-30943-8. Ch.4, pps 147 et seq. A Roundabout Route to Geometric Algebra
• ^a Liang, Kuo Kan (2018). "Efficient conversion from rotating matrix to rotation axis and angle by extending Rodrigues' formula". arXiv:1810.02999 [cs].

External links[]

• Johan E. Mebius, Derivation of the Euler-Rodrigues formula for three-dimensional rotations from the general formula for four-dimensional rotations., arXiv General Mathematics 2007.
• For another descriptive example see: http://chrishecker.com/Rigid_Body_Dynamics#Physics_Articles, Chris Hecker, physics section, part 4. "The Third Dimension" – on page 3, section ``Axis and Angle, http://chrishecker.com/images/b/bb/Gdmphys4.pdf