Learning spatial concepts from RatSLAM representations

Milford, Michael, Schulz, Ruth, Prasser, David, Wyeth, Gordon, & Wiles, Janet (2006) Learning spatial concepts from RatSLAM representations. Robotics and Autonomous Systems, 55(5), pp. 403-410.

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RatSLAM is a biologically-inspired visual SLAM and navigation system that has been shown to be effective indoors and outdoors on real robots. The spatial representation at the core of RatSLAM, the experience map, forms in a distributed fashion as the robot learns the environment. The activity in RatSLAM’s experience map possesses some geometric properties, but still does not represent the world in a human readable form. A new system, dubbed RatChat, has been introduced to enable meaningful communication with the robot. The intention is to use the “language games” paradigm to build spatial concepts that can be used as the basis for communication. This paper describes the first step in the language game experiments, showing the potential for meaningful categorization of the spatial representations in RatSLAM.

Impact and interest:

17 citations in Scopus
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12 citations in Web of Science®

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ID Code: 32814
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Spatial coceptyalization, RatSLAM, SLAM, Experience mapping
DOI: 10.1016/j.robot.2006.12.006
ISSN: 0921-8890
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 23 Jun 2010 00:54
Last Modified: 09 Dec 2014 05:52

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