| Abstract | dc.description.abstract | In current visual SLAM methods, pointlike
landmarks (As in Filliat and Meyer (Cogn
Syst Res 4(4):243–282, 2003), we use this expression
to denote a landmark generated by a point
or an object considered as punctual.) are used
for representation on maps. As the observation
of each point-like landmark gives only angular
information about a bearing camera, a covariance
matrix between point-like landmarks must be estimated
in order to converge with a global scale
estimation. However, as the computational complexity
of covariance matrices scales in a quadratic
way with the number of landmarks, the maximum
number of landmarks that is possible to
use is normally limited to a few hundred. In this
paper, a visual SLAM system based on the use
of what are called rigid-body 3D landmarks is
proposed. A rigid-body 3D landmark represents
the 6D pose of a rigid body in space (position
and orientation), and its observation gives fullpose
information about a bearing camera. Each rigid-body 3D landmark is created from a set of N
point-like landmarks by collapsing 3N state components
into seven state components plus a set of
parameters that describe the shape of the landmark.
Rigid-body 3D landmarks are represented
and estimated using so-called point-quaternions,
which are introduced here. By using rigid-body
3D landmarks, the computational time of an
EKF-SLAM system can be reduced up to 5.5%, as
the number of landmarks increases. The proposed
visual SLAM system is validated in simulated and
real video sequences (outdoor). The proposed
methodology can be extended to any SLAM system
based on the use of point-like landmarks,
including those generated by laser measurement. | es_CL |
