Appearance-Based Minimalistic Metric Slam

Paul E. Rybski, Stergios I. Roumeliotis, Maria Gini, Nikolaos Papanikolopoulos

Research output: Contribution to conferencePaperpeer-review

16 Scopus citations


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.

Original languageEnglish (US)
Number of pages6
StatePublished - 2003
Event2003 IEEE/RSJ International Conference on Intelligent Robots and Systems - Las Vegas, NV, United States
Duration: Oct 27 2003Oct 31 2003


Other2003 IEEE/RSJ International Conference on Intelligent Robots and Systems
Country/TerritoryUnited States
CityLas Vegas, NV


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