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Using sketch-maps for robot navigation: interpretation and matching
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0002-3079-0512
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0001-8658-2985
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0003-0217-9326
2016 (English)In: 2016 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), New York: Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 252-257Conference paper, Published paper (Refereed)
Abstract [en]

We present a study on sketch-map interpretationand sketch to robot map matching, where maps have nonuniform scale, different shapes or can be incomplete. For humans, sketch-maps are an intuitive way to communicate navigation information, which makes it interesting to use sketch-maps forhuman robot interaction; e.g., in emergency scenarios.

To interpret the sketch-map, we propose to use a Voronoi diagram that is obtained from the distance image on which a thinning parameter is used to remove spurious branches. The diagram is extracted as a graph and an efficient error-tolerant graph matching algorithm is used to find correspondences, while keeping time and memory complexity low.

A comparison against common algorithms for graph extraction shows that our method leads to twice as many good matches. For simple maps, our method gives 95% good matches even for heavily distorted sketches, and for a more complex real-world map, up to 58%. This paper is a first step toward using unconstrained sketch-maps in robot navigation.

Place, publisher, year, edition, pages
New York: Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 252-257
Keywords [en]
sketch, sketch-map, human robot interface, HRI, graph matching
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-53826DOI: 10.1109/SSRR.2016.7784307ISI: 000391310800039Scopus ID: 2-s2.0-85009754966ISBN: 978-1-5090-4349-1 (electronic)OAI: oai:DiVA.org:oru-53826DiVA, id: diva2:1054805
Conference
14th IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR 2016), EPFL, Lausanne, Switzerland, October 23-27, 2016
Funder
EU, Horizon 2020, ICT-23-2014 645101 SmokeBotAvailable from: 2016-12-09 Created: 2016-12-07 Last updated: 2019-10-02Bibliographically approved
In thesis
1. Helping robots help us: Using prior information for localization, navigation, and human-robot interaction
Open this publication in new window or tab >>Helping robots help us: Using prior information for localization, navigation, and human-robot interaction
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Maps are often used to provide information and guide people. Emergency maps or floor plans are often displayed on walls and sketch maps can easily be drawn to give directions. However, robots typically assume that no knowledge of the environment is available before exploration even though making use of prior maps could enhance robotic mapping. For example, prior maps can be used to provide map data of places that the robot has not yet seen, to correct errors in robot maps, as well as to transfer information between map representations.

I focus on two types of prior maps representing the walls of an indoor environment: layout maps and sketch maps. I study ways to relate information of sketch or layout maps with an equivalent metric map and study how to use layout maps to improve the robot’s mapping. Compared to metric maps such as sensor-built maps, layout and sketch maps can have local scale errors or miss elements of the environment, which makes matching and aligning such heterogeneous map types a hard problem.

I aim to answer three research questions: how to interpret prior maps by finding meaningful features? How to find correspondences between the features of a prior map and a metric map representing the same environment? How to integrate prior maps in SLAM so that both the prior map and the map built by the robot are improved?

The first contribution of this thesis is an algorithm that can find correspondences between regions of a hand-drawn sketch map and an equivalent metric map and achieves an overall accuracy that is within 10% of that of a human. The second contribution is a method that enables the integration of layout map data in SLAM and corrects errors both in the layout and the sensor map.

These results provide ways to use prior maps with local scale errors and different levels of detail, whether they are close to metric maps, e.g. layout maps, or non-metric maps, e.g. sketch maps. The methods presented in this work were used in field tests with professional fire-fighters for search and rescue applications in low-visibility environments. A novel radar sensor was used to perform SLAM in smoke and, using a layout map as a prior map, users could indicate points of interest to the robot on the layout map, not only during and after exploration, but even before it took place.

Place, publisher, year, edition, pages
Örebro: Örebro University, 2019. p. 83
Series
Örebro Studies in Technology, ISSN 1650-8580 ; 86
Keywords
graph-based SLAM, prior map, sketch map, emergency map, map matching, graph matching, segmentation, search and rescue
National Category
Computer Sciences
Identifiers
urn:nbn:se:oru:diva-75877 (URN)978-91-7529-299-1 (ISBN)
Public defence
2019-10-29, Örebro universitet, Teknikhuset, Hörsal T, Fakultetsgatan 1, Örebro, 13:15 (English)
Opponent
Supervisors
Available from: 2019-08-23 Created: 2019-08-23 Last updated: 2019-10-02Bibliographically approved

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Mielle, MalcolmMagnusson, MartinLilienthal, Achim J.

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