Recognizing Places with Weak Evidence

CSAIL Student Workshop Proceedings, 2006

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Abstract

A central problem in robot navigation is recognizing when a robot is

somewhere that it has been before. Without ``loop closing'', the

robot's position uncertainty increases without bound; consequently

navigation, map-building, and other common robot tasks become

impossible. We present an algorithm that considers groups of several dozen loop

closure hypotheses and robustly rejects the incorrect hypotheses. This

paper's central contribution is showing how to map the loop-closing

problem onto the Single Cluster Graph Partitioning (SCGP) problem,

which has an efficient solution.

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bibtex

@inproceedings{olson2006csw,
    AUTHOR     = {Edwin Olson},
    TITLE      = {Recognizing Places with Weak Evidence},
    BOOKTITLE  = {CSAIL Student Workshop Proceedings},
    YEAR       = {2006},
}