Abstract : — Mimicking human navigation is a challenging goal for autonomous robots. This requires to explicitly take into account not only geometric representation but also high-level interpretation of the environment. In this paper, we demonstrate the capability to infer a route in a global map by using semantics. Our approach relies on an object-based representation of the world automatically built by robots from spherical images. In addition, we propose a new approach to specify paths in terms of high-level robot actions. This path description provides robots with the ability to interact with humans in an intuitive way. We perform experiments on simulated and real-world data, demonstrating the ability of our approach to deal with complex large-scale outdoor environments whilst dealing with labelling errors.
Type de document :
Communication dans un congrès
IEEE Int. Conf. on Robotics and Automation, ICRA'15, May 2015, Seattle, United States
https://hal.inria.fr/hal-01122196
Contributeur : Eric Marchand
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Soumis le : mardi 3 mars 2015 - 14:04:32
Dernière modification le : vendredi 11 janvier 2019 - 15:15:01
Document(s) archivé(s) le : samedi 12 septembre 2015 - 22:41:17
Romain Drouilly, Patrick Rives, Benoit Morisset. Semantic Representation For Navigation In Large-Scale Environments. IEEE Int. Conf. on Robotics and Automation, ICRA'15, May 2015, Seattle, United States. 〈hal-01122196〉
