Robot-WSN cooperation for scalable simultaneous localization and mapping

Abstract

This chapter proposes a scalable SLAM method that uses range measurements sensed byWireless Sensor Networks (WSN) nodes. It integrates direct robot-node range measurements as well as measurements static nodes take from other nodes -internode measurements- exploitingWSN nodes capability of organizing into networks. To cope with the high number of measurements, the method adopts an PF-EIF SLAM filter, significantly more scalable and efficient than traditional schemes based on EKF. The integration and use of internode measurementscan significantly improve map and robot estimations accuracy. It can also anticipate the deployment and convergence of the Particle Filters (PFs), resulting in lower computational burden. The proposed method has been compared with traditional schemes based on EKF both in simulation and in experiments carried out in the CONET Integrated Robot-WSN Testbed.