Location Estimation Using Probability Map of a ZigBee Sensor Network

Abstract

For an on-demand robotic system, the location aware module works to provide location information of interested objects and mobile robots. This information supports various intelligent behaviors of a service robot. In this paper, a novel probability-based approach to building up a location aware system is presented. In this approach, the uncertainties and inconsistency normally suffered from received signal strength indicator (RSSI) measurements are handled with minimum prior calibration effort. By taking merely one off-line calibration measurement in a ZigBee sensor network, the inherent problem of signal uncertainty of to-be-localized nodes can be effectively resolved. The proposed RSSI-based algorithm thus has the flexibility in the thus has the flexibility in deployment of sensor nodes in various environments. The proposed algorithm has been verified in several typical environments. Comparison experiments show that the method outperforms existent algorithms in different environments.