This paper presents a method to automatically generate probabilistic graphs for path planning out of stochastic maps. A sample based technique is used to generate a set of paths from which a graph structure of the map is built. The nodes of the graph represent places in the map and the edges the paths between those places, which are labelled with the cost of traversing the edge and the probability of being navigable. We provide results of the proposed method using different types of stochastic maps such as feature-based maps, occupancy grid maps and pose graph maps.

Generation of probabilistic graphs for path planning from stochastic maps / Urcola, P.; LAZARO GRANON, MARIA TERESA; Castellanos, J. A.; Montano, L.. - (2015). (Intervento presentato al convegno 2015 European Conference on Mobile Robots (ECMR) tenutosi a Lincoln, England) [10.1109/ECMR.2015.7403770].

Generation of probabilistic graphs for path planning from stochastic maps

LAZARO GRANON, MARIA TERESA;
2015

Abstract

This paper presents a method to automatically generate probabilistic graphs for path planning out of stochastic maps. A sample based technique is used to generate a set of paths from which a graph structure of the map is built. The nodes of the graph represent places in the map and the edges the paths between those places, which are labelled with the cost of traversing the edge and the probability of being navigable. We provide results of the proposed method using different types of stochastic maps such as feature-based maps, occupancy grid maps and pose graph maps.
2015
2015 European Conference on Mobile Robots (ECMR)
Probabilistic Graphs; Graph Generation
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Generation of probabilistic graphs for path planning from stochastic maps / Urcola, P.; LAZARO GRANON, MARIA TERESA; Castellanos, J. A.; Montano, L.. - (2015). (Intervento presentato al convegno 2015 European Conference on Mobile Robots (ECMR) tenutosi a Lincoln, England) [10.1109/ECMR.2015.7403770].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/872472
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