The first step is to consider the set of transformations as a group,
in addition to a topological space.4.8 We now derive several
important groups from sets of matrices, ultimately leading to ,
the group of
rotation matrices, which is very important
for motion planning. The set of all nonsingular
real-valued matrices is called the general linear group, denoted
by
, with respect to matrix multiplication.
Each matrix
has an inverse
, which
when multiplied yields the identity matrix,
. The
matrices must be nonsingular for the same reason that 0 was removed
from
. The analog of division by zero for matrix algebra is the
inability to invert a singular matrix.
Many interesting groups can be formed from one group, , by
removing some elements to obtain a subgroup,
. To be a subgroup,
must be a subset of
and
satisfy the group axioms. We will arrive at the set of rotation
matrices by constructing subgroups. One important subgroup of
is the orthogonal group,
, which is the set of all
matrices
for which
, in which
denotes
the matrix transpose of
. These matrices have orthogonal
columns (the inner product of any pair is zero) and the determinant is
always
or
. Thus, note that
takes the inner product
of every pair of columns. If the columns are different, the result
must be 0; if they are the same, the result is
because
. The special orthogonal group,
, is the subgroup of
in which every matrix has determinant
. Another name for
is the group of
-dimensional rotation matrices.
A chain of groups,
, has been described in
which
denotes ``a subgroup of.'' Each group can also be
considered as a topological space. The set of all
matrices (which is not a group with respect to multiplication) with
real-valued entries is homeomorphic to
because
entries in the matrix can be independently chosen. For
,
singular matrices are removed, but an
-dimensional manifold is
nevertheless obtained. For
, the expression
corresponds to
algebraic equations that have to be satisfied.
This should substantially drop the dimension. Note, however, that
many of the equations are redundant (pick your favorite value for
,
multiply the matrices, and see what happens). There are only
ways (pairwise combinations) to take the inner product
of pairs of columns, and there are
equations that require the
magnitude of each column to be
. This yields a total of
independent equations. Each independent equation drops the
manifold dimension by one, and the resulting dimension of
is
, which is easily remembered as
. To obtain
, the constraint
is
added, which eliminates exactly half of the elements of
but
keeps the dimension the same.
![]() |
(4.10) |
Next, the constraint is enforced to obtain
. This
becomes
![]() |
(4.11) |
The final step is to require that
, to obtain
, the set of all 2D rotation matrices. Without this condition,
there would be matrices that produce a rotated mirror image of the
rigid body. The constraint simply forces the choice for
and
to be
and
. This throws away one of the circles from
, to obtain a single circle for
. We have finally
obtained what you already knew:
is homeomorphic to
. The
circle can be parameterized using polar coordinates to obtain the
standard 2D rotation matrix, (3.31), given in Section
3.2.2.
Steven M LaValle 2020-08-14