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 Ellekilde, Lars-Peter, Huang, S., Valls Miro, J. & Dissanayake, G. |
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Dense 3D map construction for indoor Search and Rescue
In Journal of Field Robotics (JFR 2007), vol. 24, no. 1/2, Feb, 2007, pp. 71-89, ISSN. 1556-4959
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Abstract
The main contribution of this paper is a new Simultaneous
Localization and Mapping (SLAM) algorithm for building dense
three-dimensional maps using information acquired from a range
imager and a conventional camera, for robotic search and rescue
in unstructured indoor environments. A key challenge in this
scenario is that the robot moves in 6D and no odometry information
is available. An Extended Information Filter (EIF) is used to
estimate the state vector containing the sequence of camera poses
and some selected 3D point features in the environment. Data
association is performed using a combination of Scale Invariant
Feature Transformation (SIFT) feature detection and matching,
Random Sampling Consensus (RANSAC), and least square 3D points
sets fitting. Experimental results are provided to demonstrate the
effectiveness of the techniques developed.
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