Semantic labeling of places

Stachniss, Cyrill, Martinez Mozos, Oscar, Rottmann, Axel and Burgard, Wolfram (2005) Semantic labeling of places. In: International Symposium of Robotics Research (ISRR), 12-15 October 2005, San Francisco, CA.

stachniss2005isrr.pdf - Whole Document

Item Type:Conference or Workshop contribution (Presentation)
Item Status:Live Archive


Indoor environments can typically be divided into places with different
functionalities like corridors, kitchens, offices, or seminar rooms. We believe that
such semantic information enables a mobile robot to more efficiently accomplish a
variety of tasks such as human-robot interaction, path-planning, or localization. In
this paper, we propose an approach to classify places in indoor environments into
different categories. Our approach uses AdaBoost to boost simple features extracted from vision and laser range data. Furthermore,we apply a Hidden Markov Model to take spatial dependencies between robot poses into account and to increase the robustness of the classification. Our technique has been implemented and tested on real robots as well as in simulation. Experiments presented in this paper demonstrate that our approach can be utilized to robustly classify places into semantic categories.

Additional Information:Later extended into "Using AdaBoost for Place Labeling and Topological Map Building" for the Springer book.
Keywords:mobile rootics
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G760 Machine Learning
H Engineering > H671 Robotics
Divisions:College of Science > School of Computer Science
Relation typeTarget identifier
ID Code:9585
Deposited On:28 May 2013 08:44

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