Estimation of Visual Maps with a Robot Network Equipped with Vision Sensors

Sensors

Arturo Gil¹  Óscar Reinoso²  Mónica Ballesta²  Miguel Juliá² 

[1] Universidad Miguel Hernández, Avda. de la Universidad s/n, Ed. Quorum V, r03202 Elche (Alicante), Spain;

关键词: visual SLAM;    sensor fusion;    uncertainty estimation;    cooperative robots;   

DOI  :  10.3390/s100505209

来源: mdpi

【 摘 要 】

In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM) problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment.

【 授权许可】

CC BY   
© 2010 by the authors; licensee MDPI, Basel, Switzerland.