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Appearance-based minimalistic metric SLAM (2003)
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| Venue: | IN PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ROBOTICS AND INTELLIGENT SYSTEMS (IROS), LAS VEGAS, USA |
| Citations: | 10 - 2 self |
BibTeX
@INPROCEEDINGS{Rybski03appearance-basedminimalistic,
author = {Paul E. Rybski and Stergios I. Roumeliotis and Maria Gini and Nikolaos Papanikolopoulos},
title = {Appearance-based minimalistic metric SLAM},
booktitle = {IN PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ROBOTICS AND INTELLIGENT SYSTEMS (IROS), LAS VEGAS, USA},
year = {2003},
pages = {194--199},
publisher = {}
}
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Abstract
This paper addresses the problem of Simultaneous Localization and Mapping (SLAM) for the case of very small, resource-limited robots which have poor odometry and can typically only carry a single monocular camera. We propose a modification to the standard SLAM algorithm in which the assumption that the robots can obtain metric distance/bearing information to landmarks is relaxed. Instead, the robot registers a distinctive sensor “signature”, based on its current location, which is used to match robot positions. In our formulation of this non-linear estimation problem, we infer implicit position measurements from an image recognition algorithm. The Iterated form of the Extended Kalman Filter (IEKF) is employed to process all measurements.
Keyphrases
appearance-based minimalistic metric slam implicit position measurement iterated form standard slam algorithm extended kalman filter metric distance distinctive sensor signature poor odometry image recognition algorithm resource-limited robot simultaneous localization robot position current location non-linear estimation problem single monocular camera
