Learning Hierarchical Object Maps of Non-Stationary Environments with Mobile Robots

Dragomir Anguelov, Rahul Biswas, Daphne Koller, Benson Limketkai, Sebastian Thrun · Conference on Uncertainty in Artificial Intelligence · 2002

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Summary

This paper presents an algorithm for learning object models of non-stationary objects found in office-type environments through a two-level hierarchical representation that outperforms a previously developed non-hierarchical algorithm that models objects but lacks class templates.

Type: preprint
Published: 2002-08-01
Cited by: 118
References: 22
Access: Open access
DOI: https://doi.org/10.48550/arxiv.1301.0551
arXiv: https://arxiv.org/abs/1301.0551
OpenAlex: https://openalex.org/W1519012317
Semantic Scholar: https://api.semanticscholar.org/CorpusID:51975551

Keywords

Mobile robot, Computer science, Object (grammar), Artificial intelligence, Robot

References

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A comparison of data association techniques for Simultaneous Localization and MappingAron J. Cooper — 2005
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Learning Hierarchical Object Maps of Non-Stationary Environments with Mobile Robots

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