Extending RatSLAM: The experience mapping algorithm

Abstract

In environments that are larger than the nominal area encoded by the pose cells, the RatSLAM model reuses the pose cell matrix multiple times in creating a map of the environment. This leads to several phenomena in the pose cell matrix: discontinuities where adjacent physical areas are represented by distally separate cells; multiple representations where several clusters of cells represent the same physical area; and collisions where several physical areas are represented by the same set of cells. Although the representations are topologically correct, consistent and stable, these phenomena remove the spatial relevance of the pose structure layout and hence any possibility of using it directly for tasks such as goal navigation. One approach to overcoming this problem is to create an algorithm that can maintain the inter-cell spatial information while retaining the topological correctness of the pose cell maps. The experience mapping algorithm was developed to pursue this approach. © 2008 Springer-Verlag Berlin Heidelberg.