A Split-and-Merge Segmentation Algorithm for Line Extraction in 2-D Range Images
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Cognitive maps for mobile robots-an object based approach
Robotics and Autonomous Systems
From omnidirectional images to hierarchical localization
Robotics and Autonomous Systems
Omnidirectional Vision Based Topological Navigation
International Journal of Computer Vision
Integrating grid-based and topological maps for mobile robot navigation
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
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Nowadays we frequently find big amounts of data to work with, what facilitates many robotic tasks and helps to solve perception problems. At the same time, this fact origins an interesting ongoing research problem: how to organize and arrange big sets of information to be useful in later uses. Topological mapping is a very useful tool to arrange and deal with big amounts of reference images for robotic tasks. There are many previous works on topological mapping and many others use this kind of maps for topological localization, planning and navigation. This work is focused on the problem of carefully design topological map building processes that facilitate the posterior robot tasks that use them and make them safer. We propose a new hierarchy of topological maps focused on this aspect. The experiments included in this paper were run outdoors using omnidirectional images and GPS information, and show the good topological maps obtained and how they allow robust and safer localization and navigation tasks.