URSIM: Unique Regions for Sketch Map Interpretation and Matching

We present a method for matching sketch maps to a corresponding metric map, with the aim of later using the sketch as an intuitive interface for human–robot interactions. While sketch maps are not metrically accurate and many details, which are deemed unnecessary, are omitted, they represent the top...

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Published inRobotics (Basel) Vol. 8; no. 2; p. 43
Main Authors Mielle, Malcolm, Magnusson, Martin, Lilienthal, Achim
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 2019
Subjects
Online AccessGet full text
ISSN2218-6581
2218-6581
DOI10.3390/robotics8020043

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Abstract We present a method for matching sketch maps to a corresponding metric map, with the aim of later using the sketch as an intuitive interface for human–robot interactions. While sketch maps are not metrically accurate and many details, which are deemed unnecessary, are omitted, they represent the topology of the environment well and are typically accurate at key locations. Thus, for sketch map interpretation and matching, one cannot only rely on metric information. Our matching method first finds the most distinguishable, or unique, regions of two maps. The topology of the maps, the positions of the unique regions, and the size of all regions are used to build region descriptors. Finally, a sequential graph matching algorithm uses the region descriptors to find correspondences between regions of the sketch and metric maps. Our method obtained higher accuracy than both a state-of-the-art matching method for inaccurate map matching, and our previous work on the subject. The state of the art was unable to match sketch maps while our method performed only 10% worse than a human expert.
AbstractList We present a method for matching sketch maps to a corresponding metric map, with the aim of later using the sketch as an intuitive interface for human-robot interactions. While sketch maps are not metrically accurate and many details, which are deemed unnecessary, are omitted, they represent the topology of the environment well and are typically accurate at key locations. Thus, for sketch map interpretation and matching, one cannot only rely on metric information. Our matching method first finds the most distinguishable, or unique, regions of two maps. The topology of the maps, the positions of the unique regions, and the size of all regions are used to build region descriptors. Finally, a sequential graph matching algorithm uses the region descriptors to find correspondences between regions of the sketch and metric maps. Our method obtained higher accuracy than both a state-of-the-art matching method for inaccurate map matching, and our previous work on the subject. The state of the art was unable to match sketch maps while our method performed only 10% worse than a human expert.
Author Lilienthal, Achim
Magnusson, Martin
Mielle, Malcolm
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CitedBy_id crossref_primary_10_1109_LRA_2022_3177846
crossref_primary_10_1109_LRA_2024_3522838
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Snippet We present a method for matching sketch maps to a corresponding metric map, with the aim of later using the sketch as an intuitive interface for human–robot...
We present a method for matching sketch maps to a corresponding metric map, with the aim of later using the sketch as an intuitive interface for human-robot...
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SubjectTerms Algorithms
Graph matching
human-robot interaction
interface
Localization
Map interpretation
Map matching
Robots
segmentation
Sensors
Similarity measures
sketch
Topology
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Title URSIM: Unique Regions for Sketch Map Interpretation and Matching
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