Convenient Position Estimation of Distributed Sensors in Intelligent Spaces Using SLAM for Mobile Robots

Abstract

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270002/09.jpg"" width=""200"" /> Overview of the proposed method</div> Intelligent space is one in which many networked sensors are distributed. The purpose of intelligent space is to support information for human beings and robots based on the integration of sensor information. Specifically, to support location-based applications in intelligent space, networked sensors must get locations of human beings or robots. To do so, sensor locations and orientations of sensors must be known in world coordinates. To measure numerous sensor locations accurately by hand, this study focuses on estimating the locations and orientations of distributed sensors in intelligent space – but doing so automatically. We propose map sharing using distributed laser range sensors and a mobile robot to estimate the locations of distributed sensors. Comparing maps of sensor and robots, sensor locations are estimated on a global map built by SLAM of a mobile robot. An ICP matching algorithm is used to improve map matching among sensors and robots. Experimental results with actual distributed sensors and a mobile robot show that the proposed system estimates sensor locations satisfactorily and improve the accuracy of a global map built by SLAM. </span>