Learning spatial concepts from RatSLAM representations

Authors:
Michael Milford;Ruth Schulz;David Prasser;Gordon Wyeth;Janet Wiles
Affiliations:
School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Queensland 4072, Australia;School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Queensland 4072, Australia;School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Queensland 4072, Australia;School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Queensland 4072, Australia;School of Information Technology and Electrical Engineering, The University of Queensland, St Lucia, Queensland 4072, Australia
Venue:
Robotics and Autonomous Systems
Year:
2007

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Abstract

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.