RatSLAM : a hippocampal model for simultaneous localization and mapping
Milford, Michael J., Wyeth, Gordon F., & Prasser, David (2004) RatSLAM : a hippocampal model for simultaneous localization and mapping. In Proceedings of IEEE International Conference on Robotics and Automation, 2004, IEEE, Hilton New Orleans Riverside Hotel, New Orleans, LA.
The work presents a new approach to the problem of simultaneous localization and mapping - SLAM - inspired by computational models of the hippocampus of rodents. The rodent hippocampus has been extensively studied with respect to navigation tasks, and displays many of the properties of a desirable SLAM solution. RatSLAM is an implementation of a hippocampal model that can perform SLAM in real time on a real robot. It uses a competitive attractor network to integrate odometric information with landmark sensing to form a consistent representation of the environment. Experimental results show that RatSLAM can operate with ambiguous landmark information and recover from both minor and major path integration errors.
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|Item Type:||Conference Paper|
|Keywords:||SLAM, hippocampus, moblie robot|
|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)|
|Copyright Owner:||Copyright 2004 IEEE|
|Deposited On:||30 Sep 2010 09:32|
|Last Modified:||11 Aug 2011 02:55|
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