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Symbolic Place Recognition in Voronoi-Based Maps by Using Hidden Markov Models

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Abstract

This article presents a new algorithm to recognize natural distinctive places such as corridors, halls, narrowings, corridors with doors opening on the left side, etc., from indoor environments using Hidden Markov Models (HMM). HMM give a stochastic solution which can be used to make decisions on localization, navigation and path-planning. The environment is modeled as a topo-geometric map which combines topological and geometric information. This map is obtained from a Voronoi diagram using measurements of a laser telemeter. The characteristics of topo-geometric map (nodes, number of edges adjacent to nodes, slope of edges, etc.) are used to learn and to recognize the different places typical of indoor environments. This map can be used in order to resolve several problems in robotics such as localization, navigation and path-planning. Our method of place recognition is a fast and effective way for a robot to recognize typical places of indoor environments from a topo-geometric map.

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Authors and Affiliations

  1. Mechanical Department, Carlos III University, Avd. de la Universidad, 30-28911, Leganés, Madrid, Spain

    B. L. Boada

  2. System Engineering and Automation Department, Carlos III University, Avd. de la Universidad, 30-28911, Leganés, Madrid, Spain

    D. Blanco & L. Moreno

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  1. B. L. Boada
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  2. D. Blanco
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  3. L. Moreno
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Boada, B.L., Blanco, D. & Moreno, L. Symbolic Place Recognition in Voronoi-Based Maps by Using Hidden Markov Models. Journal of Intelligent and Robotic Systems 39, 173–197 (2004). https://doi.org/10.1023/B:JINT.0000015401.49928.a4

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  • DOI: https://doi.org/10.1023/B:JINT.0000015401.49928.a4

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