Lab Meeting March 16th (swem): Inverse Depth to Depth Conversion for Monocular SLAM(ICRA2007)

Authors:Javier Civera, Andrew J. Davison, J.M.M Montiel

Robotics and Automation, 2007 IEEE International Conference on
10-14 April 2007
Page(s): 2778-2783

Abstract:
Recently it has been shown that an inverse depth
parametrization can improve the performance of real-time
monocular EKF SLAM, permitting undelayed initialization of
features at all depths. However, the inverse depth parametrization
requires the storage of 6 parameters in the state vector for
each map point. This implies a noticeable computing overhead
when compared with the standard 3 parameter XYZ Euclidean
encoding of a 3D point, since the computational complexity of
the EKF scales poorly with state vector size.
In this work we propose to restrict the inverse depth
parametrization only to cases where the standard Euclidean
encoding implies a departure from linearity in the measurement
equations. Every new map feature is still initialized using the
6 parameter inverse depth method. However, as the estimation
evolves, if according to a linearity index the alternative
XYZ coding can be considered linear, we show that feature
parametrization can be transformed from inverse depth to XYZ
for increased computational efficiency with little reduction in
accuracy.
We present a theoretical development of the necessary
linearity indices, along with simulations to analyze the influence
of the conversion threshold. Experiments performed with with a
30 frames per second real-time system are reported. An analysis
of the increase in the map size that can be successfully managed
is included.

Link: http://webdiis.unizar.es/~jcivera/papers/civera_etal_icra07.pdf
Video: http://webdiis.unizar.es/~jcivera/videos/civera_etal_icra07.mp4