Combining vision and range sensors for AMCL localization in corridor environments with rectangular signs.

Abstract

Localization is widely recognized as a fundamental problem in mobile robotics. Even though robust localization methods do exist for many applications, it is difficult for them to succeed in complex environments and challenging situations. In particular, corridor-like environments present important issues for traditional range-based methods. The main contribution of this paper is the integration of new observation models into the popular AMCL ROS node, considering visual features obtained from the detection of rectangular landmarks. Visual rectangles are distinctive elements which are very common in man-made environments and should be detected and recognized in a robust manner. This hybrid approach is developed and evaluated both for the combination of an omnidirectional camera and a laser sensor (using artificial markers) and for RGB-D sensors (using natural rectangular features). For the latter, this work also introduces RIDGE, a novel algorithm for detecting projected quadrilaterals representing rectangles in images. Simulations and real world experiments are presented for both cases. As shown and discussed in the article, the proposed approach provides significant advantages for specific conditions and common scenarios such as long straight corridors.