Map learning with uninterpreted sensors and effectors
Artificial Intelligence
Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
The spatial semantic hierarchy
Artificial Intelligence
Combinatorial Algorithms: For Computers and Hard Calculators
Combinatorial Algorithms: For Computers and Hard Calculators
Exploring artificial intelligence in the new millennium
Towards a general theory of topological maps
Artificial Intelligence
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance
International Journal of Robotics Research
A Stochastic Local Search Approach to Vertex Cover
KI '07 Proceedings of the 30th annual German conference on Advances in Artificial Intelligence
Bayesian Filtering for Location Estimation
IEEE Pervasive Computing
Learning dynamics: system identification for perceptually challenged agents
Artificial Intelligence
Fast automatic compensation of under/over-exposured image regions
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
Processing natural language without natural language processing
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Pure topological mapping in mobile robotics
IEEE Transactions on Robotics
Online probabilistic topological mapping
International Journal of Robotics Research
The revisiting problem in mobile robot map building: a hierarchical bayesian approach
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Bayesian inference in the space of topological maps
IEEE Transactions on Robotics
Mapping a Suburb With a Single Camera Using a Biologically Inspired SLAM System
IEEE Transactions on Robotics
Map-based navigation in mobile robots
Cognitive Systems Research
Map-based navigation in mobile robots
Cognitive Systems Research
Local map-based exploration for mobile robots
Intelligent Service Robotics
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In topological mapping, perceptual aliasing can cause different places to appear indistinguishable to the robot. In case of severely corrupted or non-available odometry information, topological mapping is difficult as the robot is challenged with the loop-closing problem; that is to determine whether it has visited a particular place before.In this article we propose to use neighbourhood information to disambiguate otherwise indistinguishable places. Using neighbourhood information for place disambiguation is an approach that neither depends on a specific choice of sensors nor requires geometric information such as odometry. Local neighbourhood information is extracted from a sequence of observations of visited places.In experiments using either sonar or visual observations from an indoor environment the benefits of using neighbourhood clues for the disambiguation of otherwise identical vertices are demonstrated. Over 90% of the maps we obtain are isomorphic with the ground truth. The choice of the robot's sensors does not impact the results of the experiments much.