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Representing spatial knowledge in mobile cognitive systems
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-1396-0102
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
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2010 (English)In: Intelligent Autonomous Systems 11, IAS 2010, 2010, 133-142 p.Conference paper, Published paper (Refereed)
Abstract [en]

A cornerstone for cognitive mobile agents is to represent the vast body of knowledge about space in which they operate. In order to be robust and efficient, such representation must address requirements imposed on the integrated system as a whole, but also resulting from properties of its components. In this paper, we carefully analyze the problem and design a structure of a spatial knowledge representation for a cognitive mobile system. Our representation is layered and represents knowledge at different levels of abstraction. It deals with complex, crossmodal, spatial knowledge that is inherently uncertain and dynamic. Furthermore, it incorporates discrete symbols that facilitate communication with the user and components of a cognitive system. We present the structure of the representation and propose concrete instantiations.

Place, publisher, year, edition, pages
2010. 133-142 p.
Keyword [en]
Body of knowledge, Cross-modal, Integrated systems, Levels of abstraction, Mobile systems, Spatial knowledge, Spatial knowledge representations
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-34157DOI: 10.3233/978-1-60750-613-3-133Scopus ID: 2-s2.0-84871631070ISBN: 978-160750612-6 (print)OAI: oai:DiVA.org:kth-34157DiVA: diva2:419548
Conference
11th International Conference on Intelligent Autonomous Systems, IAS 2010; Ottawa, ON; Canada; 30 August 2010 through 1 September 2010
Funder
EU, FP7, Seventh Framework Programme, CogX
Note

QC 20110527

Available from: 2011-05-27 Created: 2011-05-27 Last updated: 2014-08-15Bibliographically approved
In thesis
1. Semantic Mapping with Mobile Robots
Open this publication in new window or tab >>Semantic Mapping with Mobile Robots
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

After decades of unrealistic predictions and expectations, robots have finally escaped from industrial workplaces and made their way into our homes,offices, museums and other public spaces. These service robots are increasingly present in our environments and many believe that it is in the area ofservice and domestic robotics that we will see the largest growth within thenext few years. In order to realize the dream of robot assistants performing human-like tasks together with humans in a seamless fashion, we need toprovide them with the fundamental capability of understanding complex, dynamic and unstructured environments. More importantly, we need to enablethem the sharing of our understanding of space to permit natural cooper-ation. To this end, this thesis addresses the problem of building internalrepresentations of space for artificial mobile agents populated with humanspatial semantics as well as means for inferring that semantics from sensoryinformation. More specifically, an extensible approach to place classificationis introduced and used for mobile robot localization as well as categorizationand extraction of spatial semantic concepts from general place appearance andgeometry. The models can be incrementally adapted to the dynamic changesin the environment and employ efficient ways for cue integration, sensor fu-sion and confidence estimation. In addition, a system and representationalapproach to semantic mapping is presented. The system incorporates and in-tegrates semantic knowledge from multiple sources such as the geometry andgeneral appearance of places, presence of objects, topology of the environmentas well as human input. A conceptual map is designed and used for modelingand reasoning about spatial concepts and their relations to spatial entitiesand their semantic properties. Finally, the semantic mapping algorithm isbuilt into an integrated robotic system and shown to substantially enhancethe performance of the robot on the complex task of active object search. Thepresented evaluations show the effectiveness of the system and its underlyingcomponents and demonstrate applicability to real-world problems in realistichuman settings.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2011. xiii, 52 p.
Series
Trita-CSC-A, ISSN 1653-5723 ; 2011:10
National Category
Computer Science
Identifiers
urn:nbn:se:kth:diva-34171 (URN)978-91-7501-039-7 (ISBN)
Public defence
2011-06-10, Sal F3, Lindstedtsvägen 26, KTH, Stockholm, 13:00 (English)
Opponent
Supervisors
Note
QC 20110527Available from: 2011-05-27 Created: 2011-05-27 Last updated: 2011-05-27Bibliographically approved

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Pronobis, AndrzejJensfelt, Patric

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