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- Kanji Tanaka
- Department of Human & Artifitial Intelligence Systems, Faculty of Engineering, Univ. of Fukui
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- Tomomi Nagasaka
- Department of Human & Artifitial Intelligence Systems, Faculty of Engineering, Univ. of Fukui
説明
Obtaining a compact representation of a large-size datapoint map built by mapper robots is a critical issue for recent SLAM applications. This ”map compression” problem is explored from a novel perspective of dictionary-based map compression in the paper. The primary contribution of the paper is proposal of an incremental scheme for simultaneous mapping and map-compression applications. An incremental map compressor is presented by employing a modified RANSAC map-matching scheme as well as the compact projection technique. Experiments show promising results in terms of compression speed, compactness of data and structure, as well as an application to the compression distance.
収録刊行物
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- SICE Journal of Control, Measurement, and System Integration
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SICE Journal of Control, Measurement, and System Integration 6 (1), 54-63, 2013-01-01
Informa UK Limited
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詳細情報 詳細情報について
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- CRID
- 1360002221404031744
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- ISSN
- 18849970
- 18824889
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- データソース種別
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- Crossref
- OpenAIRE