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Semi-Supervised Semantic Labeling of Adaptive Cell Decomposition Maps in Well-Structured Environments
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0003-3498-0783
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0003-3513-8854
2015 (English)In: 2015 European Conference on Mobile Robots (ECMR), Piscataway, NJ: IEEE Press, 2015Conference paper (Refereed)
Abstract [en]

We present a semi-supervised approach for semantic mapping, by introducing human knowledge after unsupervised place categorization has been combined with an adaptive cell decomposition of an occupancy map. Place categorization is based on clustering features extracted from raycasting in the occupancy map. The cell decomposition is provided by work we published previously, which is effective for the maps that could be abstracted by straight lines. Compared to related methods, our approach obviates the need for a low-level link between human knowledge and the perception and mapping sub-system, or the onerous preparation of training data for supervised learning. Application scenarios include intelligent warehouse robots which need a heightened awareness in order to operate with a higher degree of autonomy and flexibility, and integrate more fully with inventory management systems. The approach is shown to be robust and flexible with respect to different types of environments and sensor setups. © 2015 IEEE

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Press, 2015.
Keyword [en]
Continuous wavelet transforms, Feature extraction, Labeling, Robot sensing systems, Robustness, Semantics
National Category
URN: urn:nbn:se:hh:diva-29343DOI: 10.1109/ECMR.2015.7324207ISBN: 978-1-4673-9163-4ISBN: 978-1-4673-9163-15OAI: diva2:850141
7th European Conference on Mobile Robots 2015, Lincoln, United Kingdom, 2-4 September, 2015
Knowledge Foundation

This work was supported by the Swedish Knowledge Foundation and industry partners Kollmorgen, Optronic, and Toyota Material Handling Europe.

Available from: 2015-09-01 Created: 2015-09-01 Last updated: 2016-10-08Bibliographically approved
In thesis
1. Semantic Mapping in Warehouses
Open this publication in new window or tab >>Semantic Mapping in Warehouses
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis and appended papers present the process of tacking the problem of environment modeling for autonomous agent. More specifically, the focus of the work has been semantic mapping of warehouses. A semantic map for such purpose is expected to be layout-like and support semantics of both open spaces and infrastructure of the environment. The representation of the semantic map is required to be understandable by all involved agents (humans, AGVs and WMS.) And the process of semantic mapping is desired to lean toward full-autonomy, with minimum input requirement from human user. To that end, we studied the problem of semantic annotation over two kinds of spatial map from different modalities. We identified properties, structure, and challenges of the problem. And we have developed representations and accompanied methods, while meeting the set criteria. The overall objective of the work is “to develop and construct a layer of abstraction (models and/or decomposition) for structuring and facilitate access to salient information in the sensory data. This layer of abstraction connects high level concepts to low-level sensory pattern.” Relying on modeling and decomposition of sensory data, we present our work on abstract representation for two modalities (laser scanner and camera) in three appended papers. Feasibility and the performance of the proposed methods are evaluated over data from real warehouse. The thesis conclude with summarizing the presented technical details, and drawing the outline for future work.

Place, publisher, year, edition, pages
Halmstad University: Halmstad University Press, 2016. 88 p.
Halmstad University Dissertations, 23
Automation, Robotics, Mapping, Semantic Maps, Warehouse Automation
National Category
Robotics Signal Processing
urn:nbn:se:hh:diva-32170 (URN)978-91-87045-48-6 (ISBN)978-91-87045-49-3 (ISBN)
2016-09-23, Wigforssalen, Kristian IV:s väg 3, Halmstad, Sweden, 10:15 (English)
Automatic Inventory and Mapping of Stock (AIMS)
Knowledge Foundation
Available from: 2016-10-13 Created: 2016-10-08 Last updated: 2016-10-13Bibliographically approved

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Gholami Shahbandi, SaeedÅstrand, BjörnPhilippsen, Roland
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