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.
https://hal.inria.fr/hal-01122196 Contributor : Eric MarchandConnect in order to contact the contributor 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
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⟩