ICRA 2012 Paper Abstract

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Paper TuC110.1

Fernández Alcantarilla, Pablo (University of Alcalá), Yebes, Torres, José Javier (Polytechnic school. University of Alcalá), Almazán, Javier (University of Alcalá), Bergasa, Luis Miguel (University of Alcala)

On Combining Visual SLAM and Dense Scene Flow to Increase the Robustness of Localization and Mapping in Dynamic Environments

Scheduled for presentation during the Interactive Session "Interactive Session TuC-1" (TuC110), Tuesday, May 15, 2012, 14:30−15:00, Ballroom D

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on December 11, 2017

Keywords SLAM, Localization, Mapping

Abstract

In this paper, we introduce the concept of dense scene flow for visual SLAM applications. Traditional visual SLAM methods assume static features in the environment and that a dominant part of the scene changes only due to camera egomotion. These assumptions make traditional visual SLAM methods prone to failure in crowded real-world dynamic environments with many independently moving objects, such as the typical environments for the visually impaired. By means of a dense scene flow representation, moving objects can be detected. In this way, the visual SLAM process can be improved considerably, by not adding erroneous measurements into the estimation, yielding more consistent and improved localization and mapping results. We show large-scale visual SLAM results in challenging indoor and outdoor crowded environments with real visually impaired users. In particular, we performed experiments inside the Atocha railway station and in the city-center of Alcalá de Henares, both in Madrid, Spain. Our results show that the combination of visual SLAM and dense scene flow allows to obtain an accurate localization, improving considerably the results of traditional visual SLAM methods and GPS-based approaches.

 

 

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