Simultaneous Localization and Mapping in Wireless Sensor Networks

Wireless sensors became smaller and cheaper in the recent years. Applications with thousands of nodes for tracking and monitoring are now feasible. Many of them require the knowledge about the locations of the sensors. The process of localization depends on estimating the position of the features within the environment. This paper proposes a novel algorithm to localize the sensors in any environment. Unlike any other technique like conventional SLAM, this new method does not require any architecture involving non-active beacons or mobile agents, such as robot. The new algorithm is presented that uses the sensors which act as active beacons themselves. The localization uses a least squares estimation (LSE), which processes the measured distances between the sensors. The distance measured was calculated based on received signal strength indicators (RSSI). Experiments were carried out in Mica2 Motes sensor networks. The estimated locations in the experiments were less then one meter away from the true locations which is an error of less than 10% of the transmission range from the sensors.