Integrating topological and metric maps for mobile robot navigation: A statistical approach

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Integrating topological and metric maps for mobile robot navigation: A statistical approach (1998)

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by Sebastian Thrun , Jens-steffen Gutmann , Dieter Fox , Wolfram Burgard , Benjamin J. Kuipers

Venue:	In Proceedings of the AAAI Fifteenth National Conference on Artificial Intelligence
Citations:	76 - 13 self

BibTeX

@INPROCEEDINGS{Thrun98integratingtopological,
    author = {Sebastian Thrun and Jens-steffen Gutmann and Dieter Fox and Wolfram Burgard and Benjamin J. Kuipers},
    title = {Integrating topological and metric maps for mobile robot navigation: A statistical approach},
    booktitle = {In Proceedings of the AAAI Fifteenth National Conference on Artificial Intelligence},
    year = {1998}
}

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Abstract

The problem of concurrent mapping and localization has received considerable attention in the mobile robotics community. Existing approaches can largely be grouped into two distinct paradigms: topological and metric. This paper proposes a method that integrates both. It poses the mapping problem as a statistical maximum likelihood problem, and devises an efficient algorithm for search in likelihood space. It presents an novel mapping algorithm that integrates two phases: a topological and a metric mapping phase. The topological mapping phase solves a global position alignment problem between potentially indistinguishable, significant places. The subsequent metric mapping phase produces a fine-grained metric map of the environment in floating-point resolution. The approach is demonstrated empirically to scale up to large, cyclic, and highly ambiguous environments.

Keyphrases

mobile robot navigation metric map statistical approach likelihood space distinct paradigm fine-grained metric map efficient algorithm mobile robotics community statistical maximum likelihood problem floating-point resolution concurrent mapping novel mapping algorithm subsequent metric mapping phase metric mapping phase significant place ambiguous environment considerable attention global position alignment problem mapping problem topological mapping phase

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