From neurons to robots: towards efficient biologically inspired filtering and SLAM

Authors:
Niko Sünderhauf;Peter Protzel
Affiliations:
Department of Electrical Engineering and Information Technology, Chemnitz University of Technology, Chemnitz, Germany;Department of Electrical Engineering and Information Technology, Chemnitz University of Technology, Chemnitz, Germany
Venue:
KI'10 Proceedings of the 33rd annual German conference on Advances in artificial intelligence
Year:
2010

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Abstract

We discuss recently published models of neural information processing under uncertainty and a SLAM system that was inspired by the neural structures underlying mammalian spatial navigation. We summarize the derivation of a novel filter scheme that captures the important ideas of the biologically inspired SLAM approach, but implements them on a higher level of abstraction. This leads to a new and more efficient approach to biologically inspired filtering which we successfully applied to real world urban SLAM challenge of 66 km length.