From neurons to robots: Towards efficient biologically inspired filtering and SLAM
2010
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.
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