Qualitative modeling of indoor environments from visual landmarks and range data
- 25 June 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 1, 631-636
- https://doi.org/10.1109/irds.2002.1041462
Abstract
This article describes the integration in a complete navigation system of an environment modeling method based on a Generalized Voronoi Graph (GVG), relying on laser data, on the one hand, and of a localization method based on monocular vision landmark learning and recognition framework, on the other hand. Such a system is intended to work in structured environments. It is shown that the two corresponding modules - laser GVG construction and visual landmarks learning and recognition - can cooperate to complete each other, as image processing can be enhanced by some structural knowledge about the scene, whereas the GVG is annotated, even as far as its edges are concerned, by qualitative visual information.Keywords
This publication has 5 references indexed in Scilit:
- A visual landmark framework for indoor mobile robot navigationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- On the utilization of spatial structures for cognitively plausible and efficient reasoningPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Incremental topological modeling using local Voronoi-like graphsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- The Spatial Semantic HierarchyArtificial Intelligence, 2000
- A comparison of methods for representing topological relationshipsInformation Sciences - Applications, 1995