Minimalist mobile robotics: a colony-style architecture for an artificial creature
Minimalist mobile robotics: a colony-style architecture for an artificial creature
A continuous metric scaling solution for a random variable
Journal of Multivariate Analysis
The map-building and exploration strategies of a simple sonar-equipped mobile robot
The map-building and exploration strategies of a simple sonar-equipped mobile robot
Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
One-class texture classifier in the CCR feature space
Pattern Recognition Letters
A Robot That Walks; Emergent Behaviors from a Carefully Evolved Network
A Robot That Walks; Emergent Behaviors from a Carefully Evolved Network
One-class svms for document classification
The Journal of Machine Learning Research
Biomimetic navigation models and strategies in animats
AI Communications
One-class document classification via Neural Networks
Neurocomputing
International Journal of Robotics Research
One-Class Classification by Combining Density and Class Probability Estimation
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Efficient exploration of unknown indoor environments using a team of mobile robots
Annals of Mathematics and Artificial Intelligence
Visual detection of novel terrain via two-class classification
Proceedings of the 2009 ACM symposium on Applied Computing
Recognizing places using spectrally clustered local matches
Robotics and Autonomous Systems
A comparison of loop closing techniques in monocular SLAM
Robotics and Autonomous Systems
Integrating grid-based and topological maps for mobile robot navigation
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Vision-based global localization and mapping for mobile robots
IEEE Transactions on Robotics
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Loop-closing has long been identified as a critical issue when building maps from local observations. Topological mapping methods abstract the problem of how loops are closed from the problem of how to determine the metrical layout of places in the map and how to deal with noisy sensors. The typicality problem refers to the identification of new classes in a general classification context. This typicality concept is used in this paper to help a robot acquire a topological representation of the environment during its exploration phase. The problem is addressed using the INCA statistic which follows a distance-based approach. In this paper we describe a place recognition approach based on match testing by means of the INCA test. We describe the theoretical basis of the approach and present extensive experimental results performed in both a simulated and a real robot-environment system; Behaviour Based philosophy is used to construct the whole control architecture. Obtained results show the validity of the approach.