RatSLAM: a hippocampal model for simultaneous localization and mapping
Milford, M.J.
Wyeth, G.F.
Prasser, D.
Sch. of Information Technol. & Electr. Eng., Queensland Univ., Brisbane, Qld., Australia;
Abstract
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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