Building Semantic Annotated Maps by Mobile Robots

The work presented here explains a framework to build semantic annotated maps from laser range measurements of a mobile robot. A hand-crafted and a learning classifier is explained. Two alternative methods to aggregate the resulting class membership vectors into a grid map have been developed and are presented. Both alternative methods will be motivated and described in detail and discussed critically. Results from simulations and real robot experiments will demonstrate the capability and the limitations of this approach to build semantic maps.

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