Mobile Robot Localization in Indoor Environments Using Multiple Wireless Technologies

Abstract

Localization is a fundamental problem that arises in many potential applications. The use of wireless technologies to perform localization has been a trend in recent years. Most existing approaches use the received signal strength indication (RSSI) to localize. In general, one of the several existing wireless standards such as ZigBee, Bluetooth or Wi-Fi, is chosen as the target standard. In this paper we present an experimental study on the use of multiple wireless technologies to perform mobile robot localization in indoor environments. We use real ZigBee and Wi-Fi compliant devices. In our study we analyse results obtained by fusing robot odometry data with distance estimations between the robot and wireless beacons. These distances are estimated based on the RSSI obtained from radio frequency (RF) signals received from those technologies compliant devices. The extended kalman filter (EKF) is used to fuse these information. We show that robots equipped with multiple wireless interfaces from different technologies can achieve better localization in regions where the coverage of one technology is reduced (e.g., we show that the robot can maintain a reasonable localization accuracy even in areas where Wi-Fi coverage is very poor, due to the presence of Zigbee sensor nodes). We also present a discussion of advantages and challenges of using multiple wireless technologies to perform localization in indoor environments.