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Semantic Representation For Navigation In Large-Scale Environments

Romain Drouilly 1, 2 Patrick Rives 2 Benoit Morisset 1 
2 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
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.
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Submitted on : Tuesday, March 3, 2015 - 2:04:32 PM
Last modification on : Thursday, January 20, 2022 - 4:20:31 PM
Long-term archiving on: : Saturday, September 12, 2015 - 10:41:17 PM


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  • HAL Id : hal-01122196, version 1


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⟩



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