A collaborative method for the localization of Wireless Sensor Network

Accurate and low-cost sensor localization is a critical requirement for the deployment of wireless sensor networks in a wide variety of applications. This paper presents a new method for the localization of a wireless sensor network (WSN) by means of collaboration with a robot, using both Monte Carlo and Kalman filtering techniques. The proposed methods are demonstrated in a laboratory environment where stationary camera nodes self-localized in real-time by observing Pioneer robots moving about within their field of view. The robots take observations of surveyed beacons in the environment and provide estimates of their poses to the rest of the network. The paper includes several implementation aspects and experimental results.