Simultaneous localization and mapping of Robot in Wireless Sensor Network

This paper presents a method for SLAM in Robot and Wireless Sensor Network (WSN) System using Bayes framework. A mobile robot equipped with sensor measuring the range to WSN nodes by Received Signal Strength Indicator (RSSI) can simultaneously localize itself as well as locate the sensor nodes of WSN. We adopted an algorithm based Rao-Blackwellized Particle Filter (RBPF) to integrate measurements from the different nodes over time while the robot movies in the environment. Each particle contains an estimation robot pose and a set of auxiliary filters estimating the position of sensor nodes, one for each sensor node which had been observed by robot. The auxiliary filter can switch from Particle Filter in the initial stage to EKF in the subsequent stage due to the characteristic of range-only measurement. The experiment proved the efficiency and practicality of the algorithm.