Automatic extraction of structural representations of environments

Abstract

Robots need a suitable representation of the surrounding world to operate in a structured but dynamic environment. State-of-the-art approaches usually rely on a combination of metric and topological maps and require an expert to provide the knowledge to the robot in a suitable format. Therefore, additional symbolic knowledge cannot be easily added to the representation in an incremental manner. This work deals with the problem of effectively binding together the high-level semantic information with the low-level knowledge represented in the metric map by introducing an intermediate grid-based representation. In order to demonstrate its effectiveness, the proposed approach has been experimentally validated on different kinds of environments.